破解AI时代密码，解锁全新数据增量

Steve Su (MongoDB北亚区高级副总裁 苏玉龙)
August 22, 2023 | Updated: August 23, 2023

有人将数据比喻为AI时代的智能燃料。

当下，生成式AI席卷科技领域，数据库如何加速走向AI Ready？

AI/ML的快速发展对底层的数据支持提出了新的考验，数据的多类型、高质量、处理速度和深度分析直接影响了其商业价值。

全行业的开发者都正聚焦于打造AI驱动型应用程序，而核心痛点在于：如何构建更具灵活性和可扩展性的数据模型？

相信，2023年8月29日和8月31日，我们登陆北京和深圳的MongoDB用户大会将会为大家带来最新答案。

会上，多位来自MongoDB的资深专家将进行主题演讲，带来关键行业洞见——全面拥抱AI，构建智能世界的现代化应用；同时，MongoDB 7.0新版本将震撼发布，开发者可以获得集成丰富工具的统一平台，改善开发体验，对应用负载进行现代化改造。我们将对MongoDB 7.0相关新技术、新功能进行详细解读。

每天数以万计的客户将MongoDB用于他们的应用程序，但是，每个行业和企业都有自己独特的挑战和需求。为了更好促进行业伙伴间的深度交流，我们还邀请了来自阿里云、腾讯云、腾讯游戏、亚马逊云科技、谷歌云、小冰公司、WeLab汇立集团等企业的行业同仁分享使用MongoDB产品的场景、体验和成效。

作为数据库厂商，MongoDB采用的分布式基础架构适用于泛互联网应用，AI则是MongoDB近期产品业务战略的重点。此次北京、深圳用户大会是MongoDB全球系列活动的重要两站。此前，在MongoDB用户大会纽约站，MongoDB推出了一系列新产品和新计划，包括MongoDB Atlas的新功能、MongoDB Relational Migrator，携手谷歌云公布AI计划；同时，MongoDB还发布了MongoDB Atlas行业计划，并推出面向金融行业的解决方案。

IT行业中每一次重大技术的创新，都会使应用上一个新台阶，AI也会给应用领域带来无限可能性。

回到开头的问题：如何构建更具灵活性和可扩展性的数据模型？

对于AI应用，MongoDB的产品优势在于将数据就近存储在一起，大幅降低开发难度。MongoDB可以做到：数据在哪，AI驱动型应用就能运行在哪，让应用程序靠近数据，而不是让数据靠近应用程序。

破解AI时代密码，解锁全新数据增量，

8月29日、8月31日

让我们相约北京、深圳

参加这场技术盛宴、行业盛会

结伴共同创新、共赢未来！

本文作者：MongoDB北亚区高级副总裁 苏玉龙

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Empowering Automotive Developers for the Road Ahead

MongoDB 7.0 is here, and companies across industries are benefiting from being early adopters of cutting-edge data platform technology. Let’s take a closer look at the automotive industry specifically, and how many of MongoDB’s new features and capabilities can revolutionize the way automotive developers build, iterate, and scale their applications. In the fast-changing automotive landscape, development teams face the challenge of delivering compelling user experiences faster and smarter than ever before. MongoDB's developer data platform becomes a vital tool for developers striving to innovate quickly and efficiently, supporting a wide range of application use cases while streamlining development and ensuring optimal performance. MongoDB Atlas Stream Processing MongoDB Atlas Stream Processing , coming soon in private preview, will be a game-changing advantage for the automotive industry, offering real-time data insights and rapid responses to critical events. As vehicles generate an ever-increasing stream of sensor data, this capability enables automotive developers to process, analyze, and act upon data in real-time. Manufacturers and fleet management companies can monitor vehicle health, track performance, and optimize maintenance schedules on the fly, while proactive safety measures and anomaly detection ensure utmost safety for drivers and passengers. Moreover, MongoDB Atlas Stream Processing enables developers to unlock the potential of connected car applications, making real-time data processing imperative for intelligent navigation, personalized infotainment services, and efficient route planning . MongoDB Atlas Vector Search MongoDB Atlas Vector Search , currently in public preview, holds immense potential for revolutionizing the automotive industry. By utilizing vector representations of unstructured data such as audio, images, and text, MongoDB Atlas enables developers to store, index, and query data based on similarities in high-dimensional vector spaces alongside operational data. For the automotive industry, this means unlocking a world of possibilities in data analysis, anomaly detection, and predictive maintenance. In fact, as mentioned in the MongoDB.local Chicago keynote , a top 10 auto manufacturer leveraged Vector Search to enable engine diagnostics based on engine audio. Watch the video below to learn more. Atlas Vector Search empowers automotive developers to create smarter, data-driven applications that deliver more relevant and accurate insights, ultimately enhancing the driving experience and safety for all. MongoDB Atlas Vector Search allows manufacturers to query and qualify possible equipment and product failure causes and get AI-generated recommendations on how to adjust operational parameters and extend the life of their equipment and products. The automotive industry thrives on innovation and efficiency, and Atlas Vector Search opens new avenues for optimizing vehicle performance, predicting maintenance needs, and enhancing overall user experiences on the road. MongoDB Relational Migrator In the ever-evolving automotive industry, legacy relational databases often pose challenges in scalability, flexibility, and performance. Relational databases are very prevalent in the manufacturing industry and hinder innovation due to rigid data models and limited scalability. MongoDB Relational Migrator addresses these pain points by assisting with several critical steps in the path to modernization for automotive developers. By migrating data from common relational databases to MongoDB, automotive companies can break free from the limitations of legacy systems and embrace the full potential of a NoSQL database . This migration process streamlines data transfer, offers valuable data modeling recommendations, and empowers developers to refactor applications quickly and efficiently. Embracing MongoDB's flexible document data model optimizes performance, scales applications effortlessly, and unlocks the potential for real-time analytics, enabling the industry to stay ahead in the race for innovation. MongoDB Relational Migrator becomes a catalyst for driving transformative change in the automotive sector, enabling faster and more efficient data processing for mission-critical applications and paving the way for sophisticated AI-driven solutions. As automotive companies embrace data-driven insights and strive to deliver unparalleled user experiences, MongoDB Relational Migrator empowers the industry to leverage the full potential of NoSQL databases, enabling automotive applications to zoom ahead in the fast lane of innovation. MongoDB 7.0 promises to be a game-changer for developers across industries , empowering them to build innovative, scalable, and secure applications that drive the future. With the power of MongoDB, developers can accelerate their journey toward automotive innovation and build the vehicles and experiences of tomorrow. Watch the full MongoDB.local lineup to learn more .

August 22, 2023
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3 Ways MongoDB EA Azure Arc Certification Serves Customers

One reason more than 50,000 customers across industries choose MongoDB is the freedom to run anywhere—across major cloud providers, on-premises in data centers, and in hybrid deployments. This is why MongoDB is always working to meet customers where they are. For example, many customers choose MongoDB Atlas (which is available in more than 115 cloud regions across major cloud providers) for a fully managed experience. Other customers choose MongoDB Enterprise Advanced (EA) to self-manage their database deployments to meet specific on-premises or hybrid requirements. To that end, we’re pleased to announce that MongoDB EA is one of the first certified Microsoft Azure Arc-enabled Kubernetes applications, which provides customers even more choice of where and how they run MongoDB. Customer adoption of Azure Arc has grown by leaps and bounds. This new certification, and the launch of MongoDB EA as an Arc-enabled Kubernetes application on Azure Marketplace , means that more customers will be able to leverage the unparalleled security, availability, durability, and performance of MongoDB across environments with the centralized management of their Kubernetes deployments. We are very excited to have MongoDB available for our customers on the Azure Marketplace. By extending Azure Arc’s management capabilities to your MongoDB deployments, customers gain the benefit of centralized governance, enhanced security, and deeper insights into database performance. Azure Arc makes hybrid database management with MongoDB efficient and consistent. Collaboration between MongoDB and Microsoft represents an opportunity for many of our customers to further accelerate their digital transformation when building enterprise-class solutions with Azure Arc. Christa St Pierre, Partner Group Manager, Azure Edge Devices, Microsoft Here are three ways the launch of MongoDB EA on Azure Marketplace for Arc-enabled Kubernetes applications gives customers greater flexibility. 1. MongoDB EA supports multi-Kubernetes cluster deployments, simplifies management MongoDB Enterprise Advanced seamlessly integrates market-leading MongoDB capabilities along with robust enterprise support and tools for self-managed deployments at any scale. This powerful solution includes advanced automation, comprehensive auditing, strong authentication, reliable backup, and insightful monitoring capabilities, all of which work together to ensure security compliance and operational efficiency for organizations of any size. The relationship between MongoDB and Kubernetes is one of strong synergy. With Kubernetes, MongoDB EA really can run anywhere, such as a single deployment spanning on-premises and more than one public cloud Kubernetes cluster. Customers can use the MongoDB Enterprise Kubernetes Operator, a key component of MongoDB Enterprise Advanced, to simplify the management and automation of self-managed MongoDB deployments in Kubernetes. This includes tasks like creating and updating deployments, managing backups, and integrating with various Kubernetes services. The ability of the MongoDB Enterprise Kubernetes Operator to deploy and manage MongoDB deployments that span multiple Kubernetes clusters significantly enhances resilience, improves disaster recovery, and minimizes latency by allowing data to be co-located closer to where it is needed, ensuring optimal performance and reliability. 2. Azure Arc complements MongoDB EA, providing centralized management While MongoDB Enterprise Advanced is already among a select group of databases capable of operating across multiple Kubernetes clusters , it is now also supported in Azure Arc-enabled Kubernetes environments. Azure Arc enables the standardized management of Kubernetes clusters across various environments—including in Azure, on-premises, and even other clouds—while harnessing the power of Azure services. Azure Arc accomplishes this by extending the Azure control plane to standardize security and governance across a wide range of resources and locations. For instance, organizations can centrally monitor all of the Azure Arc-enabled Kubernetes clusters using Azure Monitor for containers , or they can enforce threat protection at scale using Microsoft Defender for Kubernetes. This centralized control significantly reduces the complexity of managing Kubernetes clusters running anywhere, as customers can oversee all resources and apply consistent security and compliance policies across their hybrid environment. 3. Customers can leverage the resilience of MongoDB EA and the centralized governance of Azure Arc Together, these solutions empower organizations to build robust applications across a wide array of environments, whether on-premises or in multi-cloud settings. The combination of MongoDB Enterprise Advanced and the MongoDB Enterprise Operator simplifies the deployment of MongoDB across Kubernetes clusters, allowing organizations to fully leverage enhanced resilience and geographic distribution that surpasses the capabilities of a single Kubernetes cluster. Azure Arc further enhances this synergy by providing centralized management for all of these Kubernetes clusters, regardless of where they are running; for customers running entirely in the public cloud, we recommend using MongoDB’s fully managed developer data platform, MongoDB Atlas. If you’re interested in learning more, we invite you to explore the Azure Marketplace listing for MongoDB Enterprise Advanced for Arc-enabled Kubernetes applications. Please note that aside from use for evaluation and development purposes, this offering requires the purchase of a MongoDB Enterprise Advanced subscription. For licensing inquiries, we encourage you to reach out to MongoDB at https://www.mongodb.com/contact to secure your license and to begin harnessing the full potential of these powerful solutions.

November 19, 2024