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데일리샷, MongoDB Atlas로 스마트 주류 검색 서비스를 혁신하다

주류 시장에 불어온 새로운 바람 일부 전통주를 제외하고 오프라인 판매만 가능했던 한국 주류 시장은 2020년 온라인 판매 규제가 개정되면서 새로운 전환점을 맞이했습니다. 앱으로 언제 어디서나 원하는 주류를 주문할 수 있는 스마트 오더 서비스는 한국 소비자가 즐겨 찾는 새로운 주류 구매 방식으로 자리 잡으며 일상 전반에 편리함을 가져왔습니다. 데일리샷(Dailyshot) 은 이러한 변화를 선도적으로 이끌며 주류 경험의 새로운 기준을 정립한 국내 1위 온라인 주류 플랫폼입니다. 2020년 하반기 발빠르게 서비스를 시작한 데일리샷은 앱 기반 주류 스마트 오더 서비스를 통해 누구나 프리미엄 주류를 둘러보고 합리적인 가격으로 구매하며 매장이나 택배 등 선호하는 방식으로 수령할 수 있는 플랫폼을 제공하고 있습니다. 데이터 관리와 비즈니스 구현에 대한 고민 소비자의 주류 구매 과정 전반에서 접근성을 높일 방법을 고민하던 데일리샷은 비즈니스 성장에 따라 앱 내 검색 기능을 고도화하고 방대한 상품 종류와 픽업지 데이터를 효과적으로 관리하기 위한 전문적인 기술이 필요했습니다. 가령 고객과 가까운 동네나 주류 픽업을 희망하는 지역을 선택하기 위해서는 필터 기능이 필수적입니다. 그러나 데일리샷이 기존 사용하던 인메모리(in-memory) 데이터베이스의 Geospatial 기능은 간단한 필터링을 지원하지 않아 추가적인 서버 자원이 소모되며 비용 증가와 API 응답 지연을 야기했습니다. 또한 데일리샷의 기존 프레임워크 상에서 상품 검색을 위한 MySQL의 full-text search 기능을 사용할 수 없어 추가 리소스를 도입해야 했습니다. 상세한 검색결과를 얻기 위해서는 브랜드나 상품명, 전통주, 와인과 같은 주종, 카테고리 등 다양한 요소를 고려한 데이터 구조를 구축해야 합니다. 그러나 스타트업의 특성 상 추가 리소스를 부담하면서 full-text search를 위한 관리 구조를 만들 인력도 녹록치 않은 상황이었습니다. 데일리샷은 세계 각국의 다양한 주류를 제공하고 있기에 주문 및 픽업 방식 역시 다양합니다. 같은 상품이라도 해외 직구, 직접 픽업 등 고객의 주문 방식에 따라 옵션이 다르기 때문에 관리해야 하는 데이터가 많고 복잡합니다. 기존 사용 중인 RDBMS에서 이 같이 다양한 옵션을 아우르는 상품 테이블을 종합하는 것은 비용과 시간 모두 상당한 자원 낭비를 가져왔으며, 고객에게 데이터를 제공하기까지 상당한 시간이 소요됐습니다. 데일리샷이 제공하는 주류 픽업 및 상품 검색 서비스 성공적인 검색 서비스 고도화를 위한 여정 서비스와 고객경험 개선을 위해 고민하던 데일리샷은 기존 사용 중인 AWS를 기반으로 MongoDB Atlas를 도입했습니다. 먼저 데일리샷은 MongoDB Atlas에서 바로 컬렉션과 쿼리를 생성해 필터링을 위한 Geospatial 기능을 간편하게 구현하며 지연시간을 기존 0.3-0.5에서 0.1초로 최소화하고, MongoDB Atlas Search로 full-text search를 위한 준비를 빠르게 마칠 수 있었습니다. 최희재 데일리샷 CTO는 “다른 경쟁 서비스들과 비교하며 고심한 결과, 학습 곡선이나 유지 보수 효율성 측면에서 MongoDB Atlas Search가 우세했다”며 “MongoDB Atlas Search는 기존 사용하던 MySQL의 full-text search와 차이가 있지만 MongoDB가 제공하는 상세 가이드라인을 기반으로 쉽게 적용할 수 있었다. 기능 개발부터 서비스 배포까지 전 과정을 불과 2주만에 완료하며 고객들에게 빠르게 신기능을 선보일 수 있었다”고 강조했습니다. 최희재 CTO는 특히 MongoDB의 full-text search 기능이 검색을 위한 인덱스 구성이 쉽고 MongoDB Atlas Dashboard나 MongoDB Compass와 같은 GUI(Graphical User Interface)로 구성할 수 있다는 점을 매력 요소로 꼽았습니다. 데일리샷은 추후 Atlas Search를 서비스 전반에 도입해 퍼지 검색(fuzzy search), 자동 완성(autocomplete) 등 다양한 검색 관련 기능에 접목할 계획입니다. 독보적인 주류 경험을 제공하는 기업으로 성큼 나아가다 MongoDB Atlas 및 MongoDB Atlas Search 도입 후 데일리샷의 고객경험은 눈에 띄게 개선됐습니다. 원하는 검색 결과를 얻지 못하는 검색 실패율이 더욱 낮아졌고, Voice of Customer(VoC)를 통한 검색 관련 기술 요구 사항의 90%를 해결할 수 있었습니다. 또한 MongoDB 도입 후 RDB 인프라 자원의 사용이 줄어들면서 비용의 20% 절감할 수 있었습니다. 최희재 CTO는 “MongoDB Korea가 제공하는 양질의 기술은 물론 문제 발생 시 빠르고 정확하게 대응할 수 있도록 지원하는 점이 인상 깊었다”며 성공적인 MongoDB 도입에는 무엇보다 MongoDB Korea 팀의 적극적인 지원이 뒤따랐다고 강조했습니다. 이어 “기술 측면에서 MongoDB Atlas Dashboard로 간편한 모니터링과 slow 쿼리를 프로파일링 할 수 있었고, MongoDB Compass 앱을 통해 쿼리를 작성하고 테스트하며 실제 코드 적용까지의 전 과정을 신속하게 진행할 수 있었다. MongoDB에 익숙지 않는 개발자에게는 자세한 설명을 담은 기술 문서가 큰 도움이 됐다”고 덧붙였습니다. 데일리샷은 다양한 데이터를 아우르는 고도화된 검색 기능을 제공하면서 고객의 긍정적인 반응을 체감했고, 향후 유연한 insert 조건을 갖춘 MongoDB를 통해 로그 및 시각화를 구현하고 Atlas Vector Search로 더욱 개선된 검색 기능을 구축할 계획입니다. 지속적인 서비스 혁신을 통해 데일리샷은 2024년 기준 월간 활성 사용자수(MAU) 67만 명, 누적 앱 설치 수 150만 건을 기록하며 서비스 시작 3년만에 한국 최대 주류 플랫폼으로서 입지를 공고히 다지고 있습니다. 최희재 CTO는 “데일리샷은 단순히 주류를 구매할 수 있는 플랫폼에 그치지 않고 주류 시장 전반에 긍정적인 영향을 끼치는 기업이 되는 것이 목표”라며 “MongoDB와의 지속적인 협력을 바탕으로 고객의 다양한 니즈를 반영한 선도적인 서비스로 업계와 함께 성장하는 선순환 구조를 만들 것"이라며 포부를 드러냈습니다.

May 3, 2024

MongoDB Provider for Entity Framework Core Now Generally Available

We are pleased to announce that the MongoDB Provider for Entity Framework Core (EF Core) is now generally available. This allows developers using EF Core to build C# and .NET applications with MongoDB and to take advantage of our powerful developer data platform while continuing to use APIs and design patterns they already know and love. Building for the C# and .NET communities Nearly one-third of all developers use C# to build applications, with the population of C# developers reaching upwards of 10 million developers worldwide . What’s more, 39 percent of C# developers use EF Core , which is beloved as an abstraction layer to simplify working with data during development. In the past, C# developers could use MongoDB’s C# driver but didn’t have first-party support for EF Core, so some turned to community-built projects that could be helpful—but lacked official backing or ongoing support from MongoDB. With the official MongoDB Provider for EF Core now generally available, developers can confidently use C# and EF Core when building with MongoDB for production-grade workloads. Gaurav Seth, Partner Director, Product Management at Microsoft, shared his excitement about the new integration, highlighting its importance for the .NET developer community: We are pleased to deepen the relationship between .NET developers and MongoDB through the new MongoDB Provider for Entity Framework Core,” said Gaurav Seth. “This advancement bridges the gap between MongoDB and Entity Framework Core, enabling .NET developers to leverage the full spectrum of MongoDB’s capabilities within the familiar EF environment. With this integration, .NET developers can now more easily incorporate MongoDB’s powerful features into their EF-based applications, further enhancing the robustness and scalability of their solutions. Gaurav Seth, Partner Director, Product Management at Microsoft What's in the new Provider for EF Core With the general availability release, the MongoDB Provider for EF Core offers developers the following capabilities, building upon the foundational features released in the public preview: Compatibility with Entity Framework Core 8 & .NET 8: Fully compatible with the latest EF Core and .NET versions, ensuring your projects are up-to-date with the newest features and improvements. Advanced Querying and Data Operations: Provides a comprehensive suite of querying options, including complex operations and aggregates like Where, OrderBy, and ThenBy, enabling precise data retrieval and deeper analytical insights within your applications. Mapping and Configuration Flexibility: Extended mapping capabilities for properties and entities, including support for various data types and composite keys, providing greater flexibility and precision in how data is structured and stored. Array and List Handling: Improved handling of arrays and lists, enabling more complex data structures to be easily managed and manipulated within your applications. Logging: Enhanced logging for better visibility of operations. We will continue to offer support for the following capabilities launched in the Public Preview: Support for code-first workflows : Allows users to build without an initial database; you create the classes for your application and then match your data model to the classes, not the other way around. Basic CRUD methods: Basic create, read, update, and delete (CRUD) operations are supported. String and numeric type operators: String and numeric type operators needed for basic CRUD operations will be supported. We anticipate supporting more complex operators in future iterations of the Provider. Embedded documents: The Provider supports embedded documents, making it easier to store related information in the same database record. Class mapping and serialization: Your classes in C# will map to MongoDB in a predictable way, including when working with IDs as well as date and/or time values. LINQ query support: The Provider will support LINQ queries with fluent query syntax. Change tracking: The Provider allows you to track and save changes made to entities with each DbContext instance back to your MongoDB database. Benefits of using the Provider for EF Core With the MongoDB Provider for EF Core, C# developers can unlock the full power of MongoDB's developer data platform to build modern applications while leveraging a familiar API interface, query paradigm (LINQ), and design patterns. Developers looking to modernize their data layer can do so with MongoDB while remaining free from cloud vendor lock-in since MongoDB works with all major cloud providers and for multi-cloud deployments. How to get started with MongoDB Provider for Entity Framework Core All you need to do is download the MongoDB Provider for EF Core from the NuGet package manager and build a DbContext that points to a MongoDB Provider instance. The Provider connects to MongoDB and handles the rest, so you can quickly harness the joint value of EF Core and MongoDB. Learn more by diving into our documentation . After you try the new Provider for EF Core, leave us feedback . Your input is important for helping us continue to improve the product experience. Get started today to unleash the power of your data with MongoDB and EF Core.

May 3, 2024

Building the Next Big Thing Together: Announcing MongoDB’s Partners of the Year

Customers demand leading organizations to innovate, scale, and build modern applications at an unprecedented pace. At MongoDB, tens of thousands of companies in over 100 countries trust us with these critical workloads—the workloads that power their modern and gen AI applications. But MongoDB is hardly working alone. The broad MongoDB Partner Ecosystem is critical to serving customer needs across a number of industries, areas of excellence, and geographies. “Our partners are critical to MongoDB’s success. They help ensure that customers can access our technology easily and that they have the best possible experience when using MongoDB. “This is increasingly important as organizations look to innovate with generative AI, and our partners will play a big role in making this a reality,” said Alan Chhabra, Executive Vice President of Partners at MongoDB. “We work closely together all year, so it’s great to bring our partners together to celebrate everyone’s hard work and success. MongoDB’s partner awards shine a light on growth, determination, and an unwavering dedication to customer needs.” At .local NYC 2024, we’ve been thrilled to highlight MongoDB’s incredible partners in sessions, hands-on labs, and in announcements, including as part of the new MongoDB AI Application Program, which brings together industry-leading consultancies and foundation model providers, cloud infrastructure providers, and generative AI framework providers to help organizations rapidly build and deploy modern applications enriched with generative AI. We’re also very happy to announce MongoDB’s 2024 partners of the year. The 2024 list spans multiple partner types, industries, and categories and includes both established companies as well as emerging players. See below for more! Cloud - AI Partner of the Year: AWS Over the past year, AWS and MongoDB joined forces to make it even easier for customers to augment their gen AI-powered applications with enterprise data, most recently with the integration of MongoDB Atlas as a vector database in Amazon Bedrock’s fully managed Knowledge Base retrieval-augmented generation (RAG) workflow. In addition, MongoDB was named a launch partner for the AWS Generative AI Competency. With additional joint gen AI related integrations in the pipeline, there’s so much more to come! Cloud - Certified DBaaS Partner of the Year: Alibaba Alibaba Cloud consistently provides top-tier cloud services, integrating the latest MongoDB features and enhancements to deliver robust, scalable, and secure database solutions to a wide range of industries in China. Alibaba Cloud has the most up-to-date MongoDB services in China, via their ApsaraDB for MongoDB offering, and, along with their dedication to localizing products and services to meet the unique needs of the Chinese market, has solidified Alibaba Cloud’s position as a leading DBaaS provider. Cloud - Modernization Partner of the Year: Google Cloud MongoDB has partnered with Google Cloud since 2018, with MongoDB Atlas now available in 32 Google Cloud regions around the world, helping thousands of companies—like Ulta , Keller Williams , and Rent the Runway —adopt cloud-native data strategies. MongoDB and Google Cloud are fundamentally committed to breaking down data silos and ensuring that customers can build using data from any source, in any location, and on any platform. We're proud of our achievements in empowering businesses with data capabilities for digital transformations, and we are committed to further collaboration to help businesses succeed in their journeys. Cloud - Marketplace Partner of the Year: Microsoft Azure Microsoft and MongoDB are committed to empowering developers and organizations to build innovative, scalable, and intelligent applications on the Azure Marketplace. Through this partnership, Microsoft has enabled thousands of customers to leverage the power of MongoDB Atlas on Azure, the Data Developer Platform, accelerating their digital transformation journeys. Services - AI Industry Solutions: Capgemini Capgemini has developed innovative, MongoDB-based, Gen AI solutions over the last year, addressing multiple industries including insurance, banking, healthcare, retail, energy and the public sector. Capgemini is one of MongoDB’s most innovative partners, and we congratulate and thank them for translating value propositions into business value! Services - Modernization Partner of the Year: Accenture This year, Accenture collaborated with MongoDB—both internally within their Centers of Excellence (COEs) and externally—to modernize client application and data platforms. Our collaboration enhanced agility, reduced costs, and facilitated smooth integrations into multi-cloud environments. By leveraging MongoDB's modern data platform and gen AI technologies, Accenture used their modernization capabilities to deliver more efficient client outcomes. Services - Public Sector Partner of the Year: Clarity Solutions Clarity is our trusted partner for delivering quality professional services for our government customers. Clarity understands the air-gapped environments and have continuously helped MongoDB expand our footprint within various agencies in the public sector. We expect to continue this momentum! Services - Emerging Markets Partner of the Year: CloudMile In 2023, CloudMile launched a strategic partnership with MongoDB, leveraging Atlas, our cloud-native developer data platform. This partnership has resulted in both the delivery of modern application and modernization projects to customers across South East Asia. CloudMile enables their teams to convey and deliver the benefits of MongoDB Atlas, and we’re excited to continue growing our business across the region for years to come. Services - Jumpstart Partner of the Year: gravity9 gravity9 partners with MongoDB Professional Services to consistently deliver high quality Jumpstart engagements for our customers. Their work has accelerated consumption on MongoDB's data platform by consistently securing repeat business from some of our most strategic customers. Thank you gravity9! Services - Transformation Partner of the Year: McKinsey McKinsey’s transformational work with MongoDB on their Iguazio MLOps Platform makes them a fitting winner for this award. MongoDB & Iguazio provide unprecedented ease in delivery of data and data science on multi-cloud platforms. Utilizing the combination of MongoDB Cloud and Iguazio’s Data Science Platform allows for rapid implementation of data science projects. We’re thrilled to continue building with McKinsey for years to come. Services - AI Partner of the Year: Pureinsights Pureinsights, MongoDB's premier services partner for search and AI, has built one of the best RAG architectures for a large European car manufacturer using MongoDB's tech stack and by leveraging our comprehensive ecosystem for AI. Once deployed in production, the GAI solution will help this manufacturer save millions of dollars in their after sales division. Startup Program - AI Partner of the Year: Arcee Arcee, one of MongoDB’s most successful AI startup partners, specializes in training Smaller, Specialized Models (SLMs) that are tailored to customer’s specific data. They then employ metric-guided model merging to seamlessly integrate these custom-trained models with other large language models. This process not only enhances efficiency but also ensures limitless scalability across a broad spectrum of business applications, delivering exceptional performance tailored to meet diverse enterprise needs. ISV - Industry Solutions Partner of the Year: commercetools Commercetools’s world-leading composable commerce platform—fully powered by MongoDB Atlas—is driving the future of digital commerce. Through this partnership, commercetools can scale data to match the speed of your commerce experiences, processing real-time operational and analytical workloads for omnichannel and personalized commerce. Commercetools wins this award as they expand MongoDB’s reach into top retail brands, redefine digital commerce, and collaborate with us to deliver innovative solutions to the market. Technology - AI App Framework Partner of the Year: LangChain This year, LangChain and MongoDB partnered to simplify the development and deployment of gen AI applications through innovations like vector search, semantic caching, conversation history integrations, dedicated packages, and templates for MongoDB Atlas. The outstanding collaboration between LangChain and MongoDB continues to benefit our joint customers and all developers. Technology - AI Hosting Partner of the Year: Fireworks Fireworks AI and MongoDB Atlas came together this year to provide a solution for developers who want to leverage highly curated and optimized open-source models, and to combine these with their organization’s own proprietary data—and to do it all with unparalleled speed and security. Our continued partnership, including our joint go-to-market efforts, represents a milestone in our shared mission of helping developers to unlock the full potential of AI with confidence and efficiency. Congratulations Fireworks! Technology - Build with Partner of the Year: Informatica Informatica’s world-class MDM and 360 Applications leverages MongoDB to provide developers and organizations the opportunity to create data-first business applications, where data will drive the function and action of users and provide more opportunities for automation. Together, Informatica and MongoDB enable customers to efficiently create modern, cloud-native, data-driven, industry-tailored applications powered by MongoDB Atlas and with a secure foundation of trusted data from Informatica’s AI-powered MDM application. Thank you to all of our incredible Partners of the Year recipients! We are grateful to the entirety of our MongoDB partner ecosystem for their dedication in helping deliver incredible experiences for our customers. We will continue working with our partners to build and scale modern, genAI applications on MongoDB. To learn more about the MongoDB Partner Program, please visit our partners page .

May 2, 2024

Building Modern Applications Faster: New Capabilities at MongoDB.local NYC 2024

Today, we kicked off MongoDB.local NYC and unveiled new capabilities across our developer data platform. The updates and capabilities announced today pave the way for a new era of app modernization and will allow developers to unleash the full potential of transformative technology like AI. Here’s an overview of our announcements, from a comprehensive update to MongoDB to AI-powered intelligent developer experiences: This post is also available in: Deutsch , Français , Español , Português , Italiano , 한국어 , 简体中文 . Modern applications need a modern database Cutting-edge modern applications must deliver both an exceptional experience and additional revenue. To meet these demands, developers require a database solution that offers optimal performance, scale, and operational resilience—while maintaining cost efficiency. So today, we’re thrilled to announce the preview of MongoDB 8.0 —the next evolution of MongoDB’s modern database. MongoDB 8.0 is focused on delivering unparalleled performance, scalability, security, and operational resilience to support the creation of next-generation applications, including sophisticated AI-driven solutions. It provides optimal performance by dramatically increasing query performance, improving resilience during periods of heavy load, making scalability easier and more cost-effective, and making time series collections faster and more efficient. Modernizing your next application with MongoDB is now easier As application modernization projects gain momentum, migrations are becoming a pressing reality for development and database teams. Transitioning from legacy relational systems to modern databases like MongoDB is essential to keeping up with technological shifts like AI. However, modernization and migrations have many challenges, from converting complex schemas and translating large amounts of application code to keeping databases in sync during long modernization projects. Announced in June 2023, MongoDB Relational Migrator streamlines the migration process by automating tasks like schema design, data migrations, and application code generation. Maintaining data synchronization is paramount in long-running modernization projects—where legacy relational databases must coexist with MongoDB until the project is complete. Today, we are pleased to announce that MongoDB Relational Migrator is now integrated with Confluent Cloud to support long-running change data capture (CDC) sync jobs. These jobs ensure operational resilience and observability, addressing the complexities of phased transitions without the added burden of managing Apache Kafka independently. Furthermore, migrating from legacy relational databases often involves significant effort in rewriting SQL queries, stored procedures, and triggers, which has traditionally been time-consuming and difficult. Now available in public preview, an AI-powered SQL Query Converter Tool has been introduced to MongoDB Relational Migrator that automates the process of converting existing SQL queries, stored procedures, and triggers to work with MongoDB in languages like JavaScript, Java, or C#. This streamlined approach—paired with MongoDB professional services—enables a simplified migration process that can scale effectively. Helping developers build faster with confidence on MongoDB We recognize the vital role that developers play in the success of every project, which is why we’re dedicated to making their MongoDB experience as seamless as possible. Frameworks are a great way for developers to boost productivity, improve code consistency and quality, and ultimately deliver code faster. For the C# developer community, we are pleased to announce that the MongoDB Provider for Entity Framework Core (EF Core) is now generally available . This allows C# developers building with EF Core to unlock the full power of MongoDB's developer data platform—while still using the EF Core APIs and design patterns they already know and love. And, recognizing the needs of the PHP community, we’re also proud to introduce the Laravel Aggregation Builder . This feature simplifies the process of building complex aggregation queries within Laravel, the most popular framework among PHP developers. By enhancing the integration of MongoDB with Laravel, we aim to boost productivity and ease the complexity of query operations, ensuring PHP developers can also enjoy an optimized development experience with MongoDB. Generating queries and visualizations with AI Since its initial release in 2015, MongoDB Compass has helped developers quickly build and debug queries and aggregations for their application code. Today, MongoDB Compass introduces an AI-powered, natural language query experience , making it even easier for developers to use MongoDB’s powerful Query API. Now generally available, this feature lets developers use natural language to generate executable MongoDB Query API syntax for everything from simple queries to sophisticated aggregations through an intelligent and guided experience. For example, a developer can input "Filter vacation rentals by location, group the remaining documents by number of bedrooms, and calculate the average nightly rental price," MongoDB Compass will suggest code to execute the stages of the aggregation pipeline. Data visualizations are a powerful way of understanding application data, and embedding charts into user-facing applications further enhances their utility and appeal to developers. However, creating visualizations is often hampered by the need for in-depth knowledge of the dataset and proficiency in using business intelligence tools—skills that many developers may not have. Now available in public preview, we introduced an easy-to-use visualization tool with generative AI capabilities in MongoDB Atlas Charts . Using natural language prompts, developers can easily render charts and build dashboards, making visualizing data and enriching their apps simple and fast. For example, developers can input ‘Show me the list of movies released in the last year sorted by genre,’ and MongoDB Atlas Charts will gather data and quickly generate the requested visualization. Today’s announcements underscore MongoDB’s commitment to helping developers innovate quickly and easily. For more about the MongoDB.local NYC 2024 updates, check out the product announcements page on our website.

May 2, 2024

Welcome to MongoDB.local NYC 2024!

AI promises to upend how enterprises operate and reach customers… if only they could first find the "On" button. Despite the tremendous promise of AI, most companies still find themselves in the experimentation phase, working through proofs of concept, hampered by unfamiliar technologies that don't work well together. But MongoDB is uniquely positioned to help developers turn all this AI noise into "signal" that benefits customers. This week at MongoDB .local NYC, thousands of developers and executives—representing Fortune 500 companies and cutting-edge startups—have gathered to discuss and demonstrate the real-world successes they've had building on MongoDB's developer data platform. MongoDB is fast becoming the industry’s go-to memory database for retrieval-augmented generation (RAG) and agentic systems, offering a unified data model across the entire AI stack. But this isn’t just a technology story, as important as that is. MongoDB also now offers essential programs and services to make AI much more accessible. In short, MongoDB is taking developers from experimentation to impact, and advancing our long-standing mission of making it easy to work with data. Demystifying AI Businesses are eager to adopt generative AI, but they don’t know where to start. The AI landscape is incredibly complex—and seems to get more so by the minute. This complexity, coupled with limited in-house AI expertise and concerns about the performance and security risks of integrating disparate technologies, is keeping too many organizations on the sidelines. MongoDB can help. To get organizations started, we’re announcing the MongoDB AI Applications Program (MAAP) . With MAAP, we give customers the blueprints and reference architectures to easily understand how to build AI applications. We also take on the heavy lifting of integrating MongoDB's developer data platform with leading AI partners like Anthropic, Cohere, Fireworks AI, Langchain, LlamaIndex, Nomic, Anyscale, Credal.ai, and Together AI, all running on the cloud provider of your choice. MAAP will be available to customers in early access starting in July. In addition to MAAP, we’re also introducing two new professional services engagements to help you build AI-powered apps quickly, safely, and cost-effectively: An AI Strategy service that leverages experts to help customers identify the highest-impact AI opportunities and to create specific plans on how to pursue them. For customers who have already identified use cases to pursue, an AI Accelerator service that brings expert consulting—from solution design through prototyping—to enable customers to execute their AI application roadmap from idea to production. Once developers get to building AI apps, they’ll find that MongoDB allows them to speak the data “language” of AI. Our developer data platform unifies all different data types alongside your real-time operational data—including source data, vector embeddings, metadata, and generated data—and supports a broad range of use cases. Not only do we give developers the most intuitive way to work with their data, we also keep improving where they can do so. Many developers first experience MongoDB in a local environment before moving to a fully managed cloud service like MongoDB Atlas. So, I'm excited to share that we will be introducing full-text search and vector search in MongoDB Community Edition later this year, making it even easier for developers to quickly experiment with new features and streamlining end-to-end software development workflows when building AI applications. These new capabilities also enable support for customers who want to run AI-powered apps on devices or on-premises. As customers begin to mature these applications, cost becomes an important consideration. Last year, we introduced dedicated nodes for Atlas Search on AWS. Using dedicated nodes, customers can isolate their vector search workloads and scale them up or down independently from operational workloads, improving performance and ensuring high availability. By giving customers workload isolation without data isolation, they can manage resources efficiently without additional complexity. Today, we’re announcing Atlas Search nodes on all three cloud providers, which customers can configure programmatically using the Atlas CLI or our Infrastructure-as-Code integrations . Learn more about how MongoDB is the best solution to the challenges posed by the fast-moving generative AI landscape . Real-time and highly performant Though AI rightly claims center stage at MongoDB .local NYC this week, it's not the only way we're helping developers. From real-time fraud detection , to predictive maintenance , to content summarization , customers need to efficiently process large volumes of high-velocity data from multiple sources. Today, we’re also announcing the general availability of Atlas Stream Processing , the public preview of Atlas Edge Server , and improved performance of time series workloads with MongoDB 8.0. Together, these capabilities enable customers to design applications that solve virtually any business challenge. Learn more about how MongoDB powers modern application requirements . These are just a few of the things we're announcing this week. Whether you’re just dipping your toes into the world of generative AI or are well on your way, MongoDB’s developer data platform, strong and diverse network of partners, and proven industry solutions will give you a competitive edge in a fast-moving market. Please take a minute to see what we've built for you, so that you can more easily build for your customers. Enjoy the conference, and we hope to see you soon! To see more announcements and get the latest product updates, visit our What’s New page. And head to the MongoDB.local hub to see where we’re stopping along our 2024 world tour.

May 2, 2024

Top AI Announcements at MongoDB.local NYC

The AI landscape is evolving so quickly that it’s no surprise customers are overwhelmed by their choices. Between foundation models for everything from text to code, AI frameworks, and the steady stream of AI-related companies being founded daily, developers and organizations face a dizzying array of AI choices. MongoDB empowers customers through a developer data platform that helps them avoid vendor lock-in from cloud providers or AI vendors in this fast-moving space. This freedom allows customers to choose the large language model (LLM) that best suits their needs - now or in the future, whether it's open source or proprietary. Today at MongoDB.local NYC, we announced many new product capabilities, partner integrations, services, and solution offering that enable development teams to get started and build customer-facing solutions with AI. This post is also available in: Deutsch , Français , Español , Português , Italiano , 한국어 , 简体中文 . Run everywhere, with whatever technology you are using in your AI stack MongoDB’s flexible document model is built on the ethos of “data that is accessed and used together is stored together.” Vectors are a natural extension of this capability, meaning customers can store their source data, metadata, and related vector embeddings in the same document. All of this is accessed and queried with a common Query API, making vector data easy to combine and work with other types of data stored within MongoDB. MongoDB Atlas—our fully managed, multi-cloud developer data platform—makes it easy to build AI-powered applications and experiences, with the breadth and depth of MongoDB’s AI partnerships and integrations—no matter which language, application framework, foundation model, or technology partner is used or preferred by developers. This year, we’re continuing to focus on our AI partnerships and integrations to make it easier for developers to build innovative applications with generative AI, including: Python and JavaScript using the dedicated Langchain-MongoDB package Python and C# Microsoft Semantic Kernel integration for Atlas Vector Search AI models from Mistral and Cohere AI models on the Fireworks AI platform Addition of Atlas Vector Search as a knowledge base in Amazon Bedrock Atlas as a datastore enabling storage, query, and retrieval using natural language in ChatGPT Atlas Vector Search as a datastore on Haystack Atlas Vector Search as a datastore on DocArray Collaboration with Google Gemini Code Assist and Amazon Q to quickly prototype new features and accelerate application development. Google Vertex AI Extension to harness natural language with MongoDB queries MongoDB integrates well with a rich ecosystem of AI developer frameworks, LLMs, and embedding providers. We continue investing in making the entire AI stack work seamlessly, enabling developers to take advantage of generative AI capabilities in their applications easily. MongoDB’s integrations and our industry-leading multi-cloud capabilities allow organizations to move quickly and avoid lock-in to any particular cloud provider or AI technology in a rapidly evolving space. Build high-performance AI applications securely and at scale Workload isolation, without data isolation, is critical for building performant, scalable AI applications. Search Nodes in MongoDB Atlas provide dedicated computing and enable users to isolate memory-intensive AI workloads for superior performance and higher availability. Users can optimize resource consumption for their use case, upsizing or downsizing the hardware for that specific node irrespective of the rest of the database cluster. Search Nodes make optimizing performance for vector search queries easy without over or under-provisioning an entire cluster. The IaC integrations with Hashicorp Terraform Atlas Provider and Cloudformation enable developers to configure and programmatically deploy Search Nodes at scale. Search Nodes are an integral part of Atlas - our fully managed, battle-tested, multi-cloud platform. Previously, we announced the availability of Search Nodes for our AWS and Google Cloud customers. We are excited to announce the preview of Search Nodes for our Azure customers at MongoDB.local NYC. Search Nodes on Atlas helps developers move faster by removing the friction of integrating, securing, and maintaining the essential data components required to build and deploy modern AI applications. Improve developer productivity with AI-powered experiences Today, we also announced new and improved releases of our intelligent developer experiences in MongoDB Compass , MongoDB Relational Migrator , and MongoDB Atlas Charts , aiming to enhance developer productivity and velocity. With the updated releases, developers can use natural language to query their data using MongoDB Compass, troubleshoot common problems during development, perform SQL-to-Query API conversion right from within MongoDB Relational Migrator , and quickly build charts and dashboards using natural language prompts in MongoDB Atlas Charts. Collectively, these intelligent experiences will help developers build differentiated features with greater control and flexibility, making it easier than ever to build applications with MongoDB. Enable development teams to get started and build customer-facing solutions faster and easier with AI MongoDB makes it easy for companies of all sizes to build AI-powered applications. To provide customers with a straightforward way to get started with generative AI, MongoDB is announcing the MongoDB AI Application Program (MAAP). Based on usage patterns for common AI use cases, customers receive a functioning application built on a reference architecture backed by MongoDB Atlas, vetted AI models and hosting solutions, technical support, and a full-service engagement led by our Professional Services team. We’re launching with an incredible group of industry-leading partners, including Anthropic, Anyscale, AWS, Cohere, Credal.ai, Fireworks.ai, Google Cloud, gravity9, LangChain, LlamaIndex, Microsoft Azure, Nomic, PeerIslands, Pureinsights, and Together AI. MongoDB is in a unique position in the market to be able to pull together such an impressive AI partner ecosystem in a single customer-focused program, and we’re excited to see how MAAP will help customers more easily go from ideation to fully functioning generative AI applications. Last year, to further enable startups to build AI solutions with MongoDB Atlas, we launched the AI Innovators Program , an extension of MongoDB for Startups , which offers an additional $5000 in Atlas credits to our AI startups. This year, we are expanding the program by introducing an AI Startup Hub , which features a curated guide for getting started with MongoDB and AI, quickstarts for MongoDB and select AI partners, and startup credit offerings from our AI partners. We provide two new AI Accelerator consulting packages for larger enterprise companies: AI Essentials and AI Implementation. While MAAP is aimed exclusively at building highly vetted reference architectures, these consulting packages allow customers to design, build, and deploy open-ended AI prototypes and solutions into their applications. Data has always been a competitive advantage for organizations, and MongoDB makes it easy, fast, and flexible to innovate with data. We continue to invest in making all the other parts of the AI stack easy for organizations: vetting top partners to ensure compatibility with different parts of the application stack, building a managed service that spans multiple clouds in operation, and ensuring the openness that's always been a part of MongoDB which avoids vendor lock-in. How does MongoDB Atlas unify operational, analytical, and generative AI data services to streamline building AI-enriched applications? Check out our MongoDB for AI page to learn more.

May 2, 2024

MongoDB Introduces Workload Identity Federation for Database Access

MongoDB Atlas customers run workloads (applications) inside AWS, Azure, and Google Cloud. Today, to enable these workloads to authenticate with MongoDB Atlas cluster—customers create and manage MongoDB Atlas database users using the natively supported SCRAM (password) and X.509 authentication mechanisms and configure them in their workloads. Customers have to manage the full identity lifecycle of these users in their applications, including frequently rotating secrets. To meet their evolving security and compliance requirements, our enterprise customers require database users to be managed within their existing identity providers or cloud providers of their choice. Workload Identity Federation will be in general availability later this month and allows management of MongoDB Atlas database users with Azure Managed Identities, Azure Service Principals, Google Service Accounts, or an OAuth2.0 compliant authorization service. This approach makes it easier for customers to manage, secure, and audit their MongoDB Atlas database users in their existing identity provider or a cloud provider of their choice and enables them to have "passwordless" access to their MongoDB Atlas databases. Along with Workload Identity Federation, Workforce Identity Federation , which was launched in public preview last year, will be generally available later this month. Workforce Identity Federation allows organizations to configure access to MongoDB clusters for their employees with single sign-on (SSO) using OpenID Connect. Both features complement each other and enable organizations to have complete control of database access for both application users and employees. Workload Identity Federation support will be available in Atlas Dedicated Clusters on MongoDB 7.0 and above, and is supported by Java, C#, Node, and Python drivers. Go driver support will be added soon. Quick steps to get started with Workload Identity Federation: Configure Atlas with your OAuth2.0 compatible workload identity provider such as Azure or Google Cloud. Configure Azure Service Principal or Google Cloud Service Accounts for the Azure or Google Cloud resource where your application runs. Add the configured Azure Service Principal or Google Cloud Service Account as Atlas database users with Federated authentication. Using Python or any supported driver inside your application, authenticate and authorize with your workload identity provider and Atlas clusters. To learn more about Workload Identity Federation, please refer to the documentation . And to learn more about how MongoDB’s robust operational and security controls protect your data, read more about our security features .

May 2, 2024

Elevating Database Performance: Introducing Query Insights in MongoDB Atlas

Today, at .local NYC, MongoDB Atlas introduced the new Query Insights tab, enhancing how users monitor, manage, and optimize their database performance directly within the Atlas UI. This new feature offers developers deeper insights into their database’s performance, with a more powerful query analysis tool and detailed namespace-level metrics for faster issue resolution and enhanced performance. Applications and workloads change over time, making it increasingly difficult to track inefficient queries that strain a database's resources. Metrics can spike for various reasons, and developers need the right tooling to determine the source of the problem so they can quickly identify and resolve the issue. MongoDB Atlas's Query Insights directly tackles these challenges by enhancing MongoDB's observability capabilities with two crucial features: Namespace Insights and an upgraded Query Profiler. Query Insights delivers performance optimization through actionable intelligence The introduction of MongoDB Atlas Query Insights demonstrates MongoDB’s commitment to advanced database management. This feature enhances our platform’s observability capabilities with detailed and actionable insights. This feature integrates Namespace Insights and an upgraded Query Profiler within a new dynamic interface, helping boost database performance by streamlining diagnostics and reducing troubleshooting times. The newly added Namespace Insights provides users with collection-level latency statistics and a comprehensive view of how the hottest collections on a cluster perform over time. This enables developers to answer "Who or what is causing the problem?” which is instrumental in identifying performance trends and prioritizing query optimizations. The enhanced cluster-centric Query Profiler introduces a more comprehensive view of slow and inefficient queries over a broader period. Having an overall view of data across the entire cluster facilitates more straightforward navigation between nodes and a longer lookback period to identify trends. This ultimately reduces troubleshooting time, thereby enhancing developer productivity and improving overall database performance. Key benefits of Query Insights Query Insights brings MongoDB Atlas users several new benefits, including: Granular telemetry: Faster identification and resolution of database issues with namespace-level latency statistics Improved observability: It is easier to spot performance trends, identify root causes, and debug applications Enhanced productivity: Reduced troubleshooting time thanks to a more comprehensive view of slow operations Try it out! The Query Insights page provides more granular insights into database performance by providing collection and operation-level details. The Namespace Insights page provides metrics for the top 20 collections by total latency. Hover over the charts to see how collections perform relative to each other over time. This information makes it easier to answer the question: “who/what is causing the problem?” Use the Query Profiler to view specific slow operations. Click on a point in the scatter plot to bring up additional metadata about each slow operation. Click on View More Details to see more metrics and metadata about each slow operation, including the app name, the operation, the plan summary, execution stats, etc. Empowering users for peak performance The launch of Query Insights in MongoDB Atlas underscores MongoDB’s commitment to enhancing our platform's observability capabilities. By providing users with the necessary tools and insights for optimal database performance, MongoDB enables developers to spend less time debugging and more time creating—lowering the total cost of ownership and maximizing efficiency, adding significant value to our users' operations. Sign up for MongoDB Atlas , our cloud database service, to see Query Insights in action, and for more information, see Monitor Query Performance .

May 2, 2024

Atlas Stream Processing is Now Generally Available!

We're thrilled to announce that Atlas Stream Processing —the MongoDB-native way to process streaming data—is now generally available, empowering developers to quickly build responsive, event-driven applications! Our team spent the last two years defining a vision and building a product that leans into MongoDB’s strengths to overcome the hard challenges in stream processing. After a decade of building stream processing products outside of MongoDB, we are using everything that makes MongoDB unique and differentiated—the Query API and powerful aggregation framework, as well as the document model and its schema flexibility—to create an awesome developer experience. It’s a new approach to stream processing, and based on the feedback of so many of you in our community, it’s the best way for most developers using MongoDB to do it. Let’s get into what’s new. This post is also available in: Deutsch , Français , Español , Português , Italiano , 한국어 , 简体中文 . What's new in general availability? Production Readiness Ready to support your production workloads, ensuring reliable and scalable stream processing for your mission-critical applications. Time Series Collection Support Emit processor results into Time Series Collections . Pre-process data continuously while saving it for historical access later in a collection type available in MongoDB Atlas built to efficiently store and query time series data. Development and Production Tiers Besides the SP30 cluster tier available during the public preview, we’re introducing an SP10 tier to provide flexibility and a cost-effective option for exploratory use cases and low-traffic stream processing workloads. Improved Kafka Support Added support for Kafka headers allows applications to provide additional metadata alongside event data. They are helpful for various stream processing use cases (e.g., routing messages, conditional processing, and more). Least Privilege Access Atlas Database Users can grant access to Stream Processing Instances and enable access to only those who need it. Read our tutorial for more information. Stream Processor Alerting Gain insight and visibility into the health of your stream processors by creating alerts for when a failure occurs. Supported methods for alerting include email, SMS, monitoring platforms like Datadog, and more . Why Atlas Stream Processing? Atlas Stream Processing brings the power and flexibility of MongoDB's document model and Query API to the challenging stream processing space. With Atlas Stream Processing, developers can: Effortlessly handle complex and rapidly changing data structures Use the familiar MongoDB Query API for processing streaming data Seamlessly integrate with MongoDB Atlas Benefit from a fully managed service that eliminates operational overhead Customer highlights Read what developers are saying about Atlas Stream Processing: At Acoustic, our key focus is to empower brands with behavioral insights that enable them to create engaging, personalized customer experiences. To do so, our Acoustic Connect platform must be able to efficiently process and manage millions of marketing, behavioral, and customer signals as they occur. With Atlas Stream Processing, our engineers can leverage the skills they already have from working with data in Atlas to process new data continuously, ensuring our customers have access to real-time customer insights. John Riewerts, EVP, Engineering at Acoustic Atlas Stream Processing enables us to process, validate, and transform data before sending it to our messaging architecture in AWS powering event-driven updates throughout our platform. The reliability and performance of Atlas Stream Processing has increased our productivity, improved developer experience, and reduced infrastructure cost. Cody Perry, Software Engineer, Meltwater What's ahead for Atlas Stream Processing? We’re rapidly introducing new features and functionality to ensure MongoDB delivers a world-class stream processing experience for all development teams. Over the next few months, you can expect to see: Advanced Networking Support Support for VPC Peering to Kafka Clusters for teams requiring additional networking capabilities Expanded Cloud Region Support Support for all cloud regions available in Atlas Data Federation Expanded Cloud Provider Support Support for Microsoft Azure Expanded Data Source and Sink Support We have plans to expand beyond Kafka and Atlas databases in the coming months. Let us know which sources and sinks you need, and we will factor that into our planning Richer Metrics & Observability Support for expanded visibility into your stream processors to help simplify monitoring and troubleshooting Expanded Deployment Flexibility Support for deploying stream processors with Terraform. This integration will help to enable a seamless CI/CD pipeline, enhancing operational efficiency with infrastructure as code. Look out for a dedicated blog in the near future on how to get started with Atlas Stream Processing and Terraform. So whether you're looking to process high-velocity sensor data, continuously analyze customer data to deliver personalized experiences, or perform predictive maintenance to increase yields and reduce costs, Atlas Stream Processing has you covered. Join the hundreds of development teams already building with Atlas Stream Processing. Stay tuned to hear more from us soon, and good luck building! Login today or check out our introductory tutorial to get started.

May 2, 2024

Atlas Edge Server is Now in Public Preview

We’re excited to announce that Atlas Edge Server is now in public preview! Any developer on Atlas can now deploy Edge Server for their connected infrastructure. Learn more in our docs or get started today. Developers value MongoDB’s developer data platform for the flexibility and ease of use of the document model, as well as for helpful tools like search and charts that simplify data management. As a crucial component of our Atlas for the Edge solution, Atlas Edge Server extends these capabilities to remote and network-constrained environments. First announced at MongoDB.local London 2023, Atlas for the Edge enables local data processing and management within edge environments and across edge devices, reducing latency, enhancing performance, and allowing for disconnection resilience. This post is also available in: Deutsch , Français , Español , Português , Italiano , 한국어 , 简体中文 . What's new in public preview? One of our top priorities is providing developers with a seamless experience when managing their data and applications. We continuously seek to enhance this experience, which is why, starting today, Atlas Edge Server can be directly downloaded, configured, and managed through the Atlas UI. Developers who deploy from the Atlas UI will be able to choose between two onboarding flows to ensure that their configuration is tailored to their needs. This includes both developers who want to connect their edge server with a MongoDB driver or client, and those who want to support connecting to the Edge Server via Device Sync. Why Atlas Edge Server? While edge computing brings data processing closer to end-users and offers substantial benefits, such as network resilience and increased security, a number of challenges inherent to edge computing can make it difficult to fully leverage. Edge computing challenges include managing complex networks, handling large volumes of data, and addressing security concerns, any of which can deter organizations from adopting edge computing. Additionally, the costs associated with building, maintaining, and scaling edge computing systems can be significant. Atlas for the Edge and Atlas Edge Server alleviate these challenges. Atlas Edge Server provides a MongoDB instance equipped with a synchronization server that can be deployed on local or remote infrastructure. It enables real-time synchronization, conflict resolution, and disconnection tolerance. This ensures that mission-critical applications and devices operate seamlessly, even with intermittent connectivity. Edge Server allows for selective synchronization of only modified fields, conserving bandwidth and prioritizing crucial data transfers to Atlas. It also maintains edge client functionality even with intermittent cloud connectivity, preventing disruptions to essential operations like inventory management and point-of-sale systems. Processing data locally reduces latency and enables rapid data insights, reducing dependency on central databases. We'll meet you at the edge The Public Preview of Atlas Edge Server underscores MongoDB’s ongoing commitment to enhancing our developer data platform for distributed infrastructures. As we continue to invest in Atlas for the Edge, MongoDB’s goal is to equip teams with a robust data solution that not only offers an exceptional developer experience but also empowers them to drive innovative solutions for their businesses and customers. Get started today , or visit the Atlas for the Edge web page to learn more about how companies are benefiting from our edge solution.

May 2, 2024

Principali annunci sull'IA a MongoDB.local NYC

Il panorama dell'IA si sta evolvendo così rapidamente che non sorprende che i clienti siano sopraffatti dalle loro scelte. Tra i modelli di fondazione per qualsiasi cosa, dal testo al codice, i framework di IA e il flusso costante di aziende legate all'IA che vengono fondate ogni giorno, gli sviluppatori e le organizzazioni si trovano di fronte a una serie vertiginosa di scelte in materia di IA. MongoDB offre maggiore potere ai clienti attraverso una piattaforma dati per sviluppatori che li aiuta a evitare il lock in con i fornitori di cloud o di IA in questo spazio in rapida evoluzione. Questa libertà consente ai clienti di scegliere l'LLM (Large Language Model) che meglio si adatta alle loro esigenze, ora o in futuro, che sia open source o proprietario. Oggi a MongoDB.local NYC abbiamo annunciato molte nuove funzionalità di prodotto, integrazioni con i partner, servizi e offerte di soluzioni che consentono ai team di sviluppo di iniziare e creare soluzioni rivolte ai clienti con l'IA. Esegui ovunque, con qualsiasi tecnologia tu stia utilizzando nel tuo stack di IA Il document model flessibile di MongoDB si basa sull'etica secondo cui "i dati a cui si accede e vengono utilizzati insieme vengono archiviati insieme". I vettori sono un'estensione naturale di questa funzionalità, il che significa che i clienti possono archiviare i dati di origine, i metadati e i relativi incorporamenti di vettori nello stesso documento. Tutto questo è accessibile e interrogabile con una API di query comune, rendendo i dati vettoriali facili da combinare e lavorare con altri tipi di dati archiviati in MongoDB. MongoDB Atlas, la nostra piattaforma dati per sviluppatori multi-cloud completamente gestita, semplifica la creazione di applicazioni ed esperienze basate sull'IA, con l'ampiezza e la profondità delle partnership e integrazioni IA di MongoDB, indipendentemente dal linguaggio, dal framework applicativo, dal modello di fondazione o dal partner tecnologico utilizzato o preferito dagli sviluppatori. Quest'anno continuiamo a concentrarci sulle nostre partnership e integrazioni con l'IA per rendere più semplice agli sviluppatori la creazione di applicazioni innovative con l'IA generativa, tra cui: Python e JavaScript utilizzando il pacchetto dedicato Langchain-MongoDB Integrazione di Microsoft Semantic Kernel in Python e C# per Atlas Vector Search Modelli di IA di Mistral e Cohere Modelli di IA sulla piattaforma Fireworks AI Aggiunta di Atlas Vector Search come Knowledge Base in Amazon Bedrock Atlas come archivio dati che consente l'archiviazione, l'interrogazione e il recupero utilizzando il linguaggio naturale in ChatGPT Atlas Vector Search come archivio dati su Haystack Atlas Vector Search come archivio dati su DocArray Collaborazione con Google Gemini Code Assist e Amazon Q per prototipare rapidamente nuove funzionalità e accelerare lo sviluppo di applicazioni. Estensione Google Vertex AI per sfruttare il linguaggio naturale con le query MongoDB MongoDB si integra bene con un ricco ecosistema di framework per sviluppatori di IA, LLM e fornitori di incorporamento. Continuiamo a investire per far sì che l'intero stack di IA funzioni perfettamente, consentendo agli sviluppatori di sfruttare facilmente le funzionalità di IA generativa nelle loro applicazioni. Le integrazioni di MongoDB e le nostre funzionalità multi-cloud leader del settore consentono alle organizzazioni di muoversi rapidamente ed evitare il lock in con qualsiasi particolare provider cloud o tecnologia IA in uno spazio in rapida evoluzione. Crea applicazioni IA ad alte prestazioni in modo sicuro e su larga scala L'isolamento del carico di lavoro, senza isolamento dei dati, è fondamentale per creare applicazioni IA performanti e scalabili. I nodi di ricerca in MongoDB Atlas forniscono elaborazione dedicata e consentono agli utenti di isolare i carichi di lavoro IA ad alta intensità di memoria per prestazioni superiori e maggiore disponibilità. Gli utenti possono ottimizzare il consumo di risorse per il loro caso d'uso, aumentando o ridimensionando l'hardware per quel nodo specifico indipendentemente dal resto del cluster di database. I nodi di ricerca semplificano l'ottimizzazione delle prestazioni per le query di ricerca vettoriale senza eseguire un provisioning eccessivo o insufficiente di un intero cluster. Le integrazioni IaC con Hashicorp Terraform Atlas Provider e Cloudformation consentono agli sviluppatori di configurare e implementare programmaticamente i nodi di ricerca su larga scala. I nodi di ricerca sono parte integrante di Atlas Search: la nostra piattaforma multi-cloud completamente gestita e testata sul campo. In precedenza, abbiamo annunciato la disponibilità dei nodi di ricerca per i nostri clienti AWS e Google Cloud . Siamo ora lieti di annunciare la disponibilità dei nodi di ricerca per i nostri clienti Azure a MongoDB.local NYC. I nodi di ricerca su Atlas aiutano gli sviluppatori a muoversi più velocemente eliminando le difficoltà legate all'integrazione, alla protezione e alla manutenzione dei componenti di dati essenziali necessari per creare e distribuire moderne applicazioni IA. Migliora la produttività degli sviluppatori con esperienze basate sull'IA Oggi abbiamo anche annunciato nuove e migliorate versioni delle nostre esperienze di sviluppo intelligenti in MongoDB Compass , MongoDB Relational Migrator e MongoDB Atlas Charts , con l'obiettivo di migliorare la produttività e la velocità degli sviluppatori. Con le versioni aggiornate, gli sviluppatori possono utilizzare il linguaggio naturale per interrogare i propri dati utilizzando MongoDB Compass, risolvere problemi comuni durante lo sviluppo, eseguire la conversione dell'API da SQL a query direttamente da MongoDB Relational Migrator e creare rapidamente grafici e dashboard utilizzando prompt in linguaggio naturale in MongoDB Atlas Charts. Nel complesso, queste esperienze intelligenti aiuteranno gli sviluppatori a creare funzionalità differenziate con maggiore controllo e flessibilità, rendendo più facile che mai la creazione di applicazioni con MongoDB. Consenti ai team di sviluppo di iniziare a creare soluzioni rivolte ai clienti in modo più rapido e semplice con l'IA MongoDB semplifica la creazione di applicazioni basate sull'IA per le aziende di tutte le dimensioni. Per fornire ai clienti un modo semplice per iniziare con l'IA generativa, MongoDB annuncia il MongoDB AI Application Program (MAAP) . In base ai modelli di utilizzo per i casi d'uso comuni dell'IA, i clienti ricevono un'applicazione funzionante costruita su un'architettura di riferimento supportata da MongoDB Atlas, modelli di IA e soluzioni di hosting verificati, supporto tecnico e un impegno a servizio completo guidato dal nostro team di servizi professionali. L'anno scorso, per consentire ulteriormente alle startup di creare soluzioni di IA con MongoDB Atlas, abbiamo lanciato l'AI Innovators Program , un'estensione di MongoDB for Startups , che offre ulteriori 5000 dollari in crediti Atlas alle nostre startup di IA. Quest'anno stiamo espandendo il programma introducendo un Hub per startup IA , che presenta una guida curata per iniziare a lavorare con MongoDB e l'IA, guide rapide per MongoDB e partner IA selezionati e offerte di crediti per startup da parte dei nostri partner IA. Forniamo due nuovi pacchetti di consulenza AI Accelerator per le aziende più grandi: AI Essentials e AI Implementation. Sebbene MAAP sia finalizzato esclusivamente alla creazione di architetture di riferimento altamente controllate, questi pacchetti di consulenza consentono ai clienti di progettare, costruire e implementare prototipi e soluzioni di IA aperti nelle loro applicazioni. I dati sono sempre stati un vantaggio competitivo per le organizzazioni e MongoDB rende facile, veloce e flessibile innovare con i dati. Continuiamo a investire nel rendere tutte le altre parti dello stack di IA facili per le organizzazioni: esaminando i migliori partner per garantire la compatibilità con diverse parti dello stack di applicazioni, costruendo un servizio gestito che si estende su più cloud in funzione e garantendo l'apertura che è sempre stata una parte di MongoDB che evita il lock in con il fornitore. In che modo MongoDB Atlas unifica i servizi dati operativi, analitici e di IA generativa per semplificare la creazione di applicazioni arricchite dall'IA? Consulta la nostra pagina MongoDB for AI per saperne di più.

May 2, 2024

Les principales annonces concernant l’IA au MongoDB.local NYC

Le paysage de l’IA évolue rapidement, et il n’est pas surprenant que les clients se sentent dépassés dans leurs choix. Entre les modèles de fondation pour tout, du texte au code, en passant par les frameworks d’IA et le flux quotidien de nouvelles entreprises liées à l’IA, les développeurs et les entreprises sont confrontés à un éventail vertigineux de choix. MongoDB autonomise les clients grâce à une plateforme de données pour les développeurs qui évite la dépendance vis-à-vis des fournisseurs de services cloud ou d’IA dans cet espace en évolution rapide. Cette liberté permet aux clients de choisir le grand modèle de langage (LLM) qui répond le mieux à leurs besoins, actuels ou futurs, qu’il soit open source ou propriétaire. Aujourd’hui, à l’occasion de la conférence MongoDB.local NYC, nous avons annoncé de nombreuses nouvelles fonctionnalités de produits, intégrations de partenaires, services et offres de solutions qui permettent aux équipes de développement de démarrer et de créer des solutions orientées client grâce à l’IA. Exécutez partout, quelle que soit la technologie que vous utilisez dans votre pile IA Le document model flexible de MongoDB repose sur la philosophie selon laquelle « les données accessibles et utilisées ensemble sont stockées ensemble ». Les vecteurs constituent une extension naturelle de cette capacité, ce qui signifie que les clients peuvent stocker leurs données sources, leurs métadonnées et les représentations vectorielles associées dans le même document. L’ensemble est accessible et interrogé à l’aide d’une API de requête commune. Les données vectorielles sont ainsi faciles à combiner et à utiliser avec d’autres types de données stockées dans MongoDB. MongoDB Atlas, notre plateforme de données multicloud pour les développeurs entièrement gérée, facilite la création d’applications et d’expériences basées sur l’IA, grâce à l’étendue et à la profondeur des partenariats et des intégrations d’IA de MongoDB, quels que soient le langage, le framework applicatif, le modèle de fondation ou le partenaire technologique choisi par les développeurs. Cette année, nous continuons à nous concentrer sur nos partenariats et les intégrations de l’IA afin que les développeurs puissent créer plus facilement des applications innovantes avec l’IA générative, en particulier : Python et JavaScript à l’aide du package dédié Langchain-MongoDB Intégration Python et C# Microsoft Semantic Kernel pour Atlas Vector Search Modèles d’IA de Mistral et Cohere Modèles d’IA sur la plateforme Fireworks AI Ajout d’Atlas Vector Search en tant que base de connaissances dans Amazon Bedrock Atlas en tant que banque de données permettant le stockage, les requêtes et la récupération en langage naturel dans ChatGPT Atlas Vector Search en tant que banque de données sur Haystack Atlas Vector Search comme banque de données sur DocArray Collaboration avec Google Gemini Code Assist et Amazon Q pour prototyper rapidement de nouvelles fonctionnalités et accélérer le développement d’applications. Extension Google Vertex AI pour exploiter le langage naturel avec les requêtes MongoDB. MongoDB s’intègre parfaitement à un riche écosystème de frameworks de développement rassemblant IA, LLM et fournisseurs d’intégration. Nous continuons à investir pour que l’ensemble de la pile IA fonctionne de manière transparente, permettant aux développeurs de tirer facilement parti des capacités de l’IA générative dans leurs applications. Les intégrations de MongoDB et nos capacités multicloud de pointe permettent aux entreprises d’agir rapidement et d’éviter de dépendre d’un fournisseur de cloud particulier ou d’une technologie d’IA spécifique dans un environnement en évolution rapide. Créez des applications d’IA hautes performances en toute sécurité et à grande échelle L’isolation des charges de travail, sans isolation des données, est essentielle pour créer des applications d’IA performantes et évolutives. Les nœuds de recherche dans MongoDB Atlas fournissent un calcul dédié et permettent aux utilisateurs d’isoler les charges de travail d’IA gourmandes en mémoire pour des performances supérieures et une disponibilité accrue. Les utilisateurs peuvent optimiser la consommation des ressources en fonction de leur cas d’utilisation, en augmentant ou en réduisant la taille du hardware pour ce nœud spécifique, sans tenir compte du reste du cluster. Les nœuds de recherche facilitent l’optimisation des performances pour les requêtes de recherche vectorielle sans avoir à sur- ou sous-approvisionner l’ensemble d’un cluster. Les intégrations IaC avec Hashicorp Terraform Atlas Provider et Cloudformation permettent aux développeurs de configurer et de déployer par programmation des nœuds de recherche à grande échelle. Les nœuds de recherche font partie intégrante d’Atlas Search, notre plateforme multicloud entièrement gérée et testée. Nous avions annoncé auparavant la disponibilité des nœuds de recherche pour nos clients AWS et Google Cloud . Nous sommes maintenant ravis d’annoncer au MongoDB.local NYC la disponibilité des nœuds de recherche pour nos clients Azure. Atlas Search aide les développeurs à travailler plus rapidement en éliminant les difficultés liées à l’intégration, à la sécurisation et à la maintenance des composants de données essentiels à la création et au déploiement d’applications d’IA modernes. Améliorez la productivité des développeurs grâce à des expériences basées sur l’IA Aujourd’hui, nous avons également annoncé de nouvelles versions améliorées de nos expériences de développement intelligentes dans MongoDB Compass , MongoDB Relational Migrator et MongoDB Atlas Charts , visant à améliorer la productivité et la rapidité des développeurs. Avec les versions mises à jour, les développeurs peuvent utiliser le langage naturel pour interroger leurs données à l’aide de MongoDB Compass, résoudre les problèmes courants pendant le développement, effectuer la conversion de requêtes d’API SQL directement depuis MongoDB Relational Migrator et créer rapidement des graphiques et des tableaux de bord à l’aide de prompts en langage naturel dans Atlas Charts. Collectivement, ces expériences intelligentes aideront les développeurs à créer des fonctionnalités différenciées avec plus de contrôle et de flexibilité, facilitant plus que jamais la création d’applications avec MongoDB. Aidez les équipes de développement à démarrer et à créer des solutions orientées client plus rapidement et plus facilement grâce à l’IA MongoDB permet aux entreprises de toutes tailles de créer facilement des applications basées sur l’IA. Afin de fournir à ses clients un moyen simple de démarrer avec l’IA générative, MongoDB annonce le MongoDB AI Application Program (MAAP) . Sur la base de schémas d’utilisation pour des cas d’utilisation courants de l’IA, les clients reçoivent une application fonctionnelle construite sur une architecture de référence soutenue par MongoDB Atlas, des modèles d’IA et des solutions d’hébergement approuvés, un support technique et un engagement de service complet dirigé par notre équipe de services professionnels. L’année dernière, afin de permettre aux startups de développer des solutions d’IA avec MongoDB Atlas, nous avons lancé le programme AI Innovators , une extension de MongoDB for Startups , qui offre 5 000 dollars supplémentaires en crédits Atlas à nos startups spécialisées dans l’IA. Cette année, nous élargissons le programme en introduisant le programme AI Startup Hub , qui propose un guide organisé pour démarrer avec MongoDB et l’IA, des guides de démarrage rapide pour MongoDB et certains partenaires IA, ainsi que des offres de crédit de démarrage de nos partenaires IA. Nous proposons deux nouveaux packages de conseil AI Accelerator pour les grandes entreprises : AI Essentials et AI Implementation. Alors que le programme MAAP vise exclusivement à créer des architectures de référence hautement vérifiées, ces packages de conseil permettent aux clients de concevoir, de créer et de déployer des prototypes et des solutions d’IA ouvertes dans leurs applications. Les données ont toujours constitué un avantage concurrentiel pour les entreprises, et MongoDB permet d’innover facilement, rapidement et de manière flexible avec les données. Nous continuons à investir pour faciliter l’accès des entreprises à toutes les autres composantes de la pile IA : nous sélectionnons les meilleurs partenaires pour garantir la compatibilité avec les différentes parties de la pile d’applications, nous créons un service géré qui couvre plusieurs cloud en fonctionnement, et nous garantissons l’ouverture qui a toujours été au cœur de MongoDB pour éviter le verrouillage des fournisseurs. MongoDB Atlas unifie les services de données opérationnels, analytiques et d’IA générative en fournissant une plateforme unique pour gérer et analyser les données. Cela permet aux entreprises de rationaliser le processus de développement d’applications enrichies par l’IA en leur fournissant un accès facile aux données dont elles ont besoin. Consultez notre page MongoDB pour l’IA pour en savoir plus.

May 2, 2024