Resources

AI-Powered Personalization to Drive Next-Generation Media Channels

Media producers face an ever-growing level of competition. To keep users engaged, it is crucial to quickly and intelligently learn from their interactions and content consumption, deriving insights into their preferences and what content they are likely to pay for. In this webinar, we will explore how MongoDB Atlas Vector Search can be positioned at the architectural core of a modern, AI-supported media platform. View this webinar to learn about: Easy creation of intelligent content recommendations Generation of comprehensive content summaries The automatic extraction of SEO keywords from text Enhancing content visibility and search engine ranking Through examples using Python and LangChain, you'll discover how to seamlessly integrate these powerful features into your applications, helping you stay ahead of the competition.

Haunted by SQL? How MongoDB Can Save Your Database Nightmares

For decades, traditional relational databases (RDBMS) have been the foundation of data storage, born in an era when minimising storage costs was paramount. But today’s challenges are different. While storage costs have plummeted, the complexity of working with data remains a critical barrier. Developers need to move fast, innovate, and support a wide range of use cases — relational, time series, graph, document, search, and even vector search — without the inefficiencies of data duplication and silos. In this session, we’ll explore how MongoDB Atlas can help you escape the limitations of traditional SQL databases, reduce complexity, and unlock the full potential of your data to build cutting-edge applications.

What’s New in MongoDB for .NET Developers

Join Developer Advocate Luce Carter as she explores MongoDB's latest advancements for .NET and C#. In this session, you'll discover: How the C# driver lets you connect to MongoDB. How the MongoDB provider for Entity Framework Core lets developers access the full spectrum of MongoDB’s capabilities within the familiar EF environment. How to use MongoDB with Microsoft Semantic Kernel and .NET Aspire to create modern AI-powered and cloud-native apps.

Tricks to Treat Your Database: Spooky MongoDB Schema Anti-Patterns and How to Avoid Them

Designing the right database schema is an essential skill for any MongoDB developer. You've probably heard the best practices many times before, but with Halloween just around the corner, let's take a more sinister route. Instead of focusing on the "right way" to do it, we'll confront the spooky anti-patterns lurking in your database schema. We'll learn how to identify these problems and, more importantly, how to exorcise them from your schema once and for all. In this session, we'll dive into six common MongoDB schema design anti-patterns, all revolving around document sizing, and learn how to overcome them.

The Cloud, AI and Financial Services: How they can play together

Financial Services companies have always been at the forefront of technology and the story is no different concerning two of the latest tech trends: the move to the cloud and artificial intelligence. Financial services companies are anxious to put both to good use in their never-ending search for a competitive edge. MongoDB and PeerIslands are intimately involved in helping financial institutions meet their goals. Watch this webinar to hear experts from both companies discuss topics including: The drivers for continued digitization and how best to contain costs along the way How to take advantage of the cost and scale benefits of the cloud, while maintaining security The role of modern databases in promoting data analytics and real-time data access How AI is accelerating the move to modernization, playing a role in everything dealing with legacy code to implementing new features Maintaining a focus on business value amid all the technology buzz You will hear from: Wei You Pan: Director, Financial Services Industry Solutions at MongoDB Rajesh Rajagoppalan: President & CTO at PeerIslands Paul Desmond: Content Strategist at CIO Marketing Services

Atlas 101 eWorkshop (English)

Intro to Data Modeling for Financial Services and Insurance (APAC timezone)

With its document-oriented data model, real-time analytics capabilities, and seamless integration with other cutting-edge technologies, MongoDB has become the go-to choice for forward-thinking financial and insurance institutions. Since the relational schema and MongoDB schema are different, a question that keeps getting asked is: “I’m designing an application to do X, how do I model the data?” How you model your data early on affects the speed of development throughout your application lifecycle and can have ramifications on performance far down the line. In this webinar, we will examine the most important considerations for financial applications when making decisions about the data model that best fits your application. This session is designed to introduce developers, technologists, and technical decision-makers to the NoSQL mindset for financial organizations and to break down NoSQL data modeling for real-world workloads. We'll cover: The differences between data modeling in MongoDB vs. relational databases How to further enhance the power of the document model with schema design patterns applied to financial use cases

Comparing PostgreSQL vs. MongoDB: Which Is Better for AI Workloads?

In this webinar, we reveal results from our benchmark tests between these two different database systems. The webinar was presented by MongoDB Field CTO, Rick Houlihan, who has decades of experience working with RDBMS, PostgreSQL, and document databases like MongoDB. Watch now and find out why it’s essential to consider database platforms specifically designed to handle large, complex data structures to effectively support modern AI applications.

Intelligent Application Modernization with MongoDB Atlas and AWS

In the rapidly evolving world of technology, modernizing applications to meet current and future demands is crucial. Watch our insightful webinar, "Intelligent Application Modernization with MongoDB Atlas and AWS," where we delved into the strategic advantages and practical steps for migrating your applications to MongoDB Atlas on AWS. Sweta Dwivedi, Solutions Architect at MongoDB and Srikar Reddy Kasireddy, Solutions Architect Specialist at AWS discussed: Why migrate to MongoDB Atlas on AWS: Discover the compelling reasons to transition to MongoDB Atlas on AWS, including enhanced performance, scalability, and security, as well as opportunities for significant cost savings and operational efficiencies. Planning migration projects: Gain insights into effective planning and execution of migration projects. Learn best practices for assessing your current environment, setting realistic timelines, and managing risks to ensure a smooth and successful migration. Relational Migrator overview: Get an overview of the Relational Migrator tool, designed to streamline and simplify the migration of relational databases to MongoDB Atlas. Understand its key features, capabilities, and how it can accelerate your migration process. Amazon Q Developer: Explore Amazon Q Developer, a powerful suite of tools and services that enhance the development and deployment of applications on AWS. Learn how it integrates with MongoDB Atlas to offer a robust and scalable solution for modern application development. Live demo: Witness a live demonstration showcasing the migration process from a traditional relational database to MongoDB Atlas on AWS. See firsthand the ease of use, speed, and reliability of the tools and services discussed. Watch this webinar today and unlock the full potential of your applications with MongoDB Atlas and AWS. Equip yourself with the knowledge and tools needed to lead your organization through a seamless and intelligent application modernization journey.

Atlas 101 eWorkshop (English)

Atlas 101 eWorkshop (English)

Building Agentic RAG Apps with MongoDB, Unstructured, and LangGraph

Whether you are building advanced search applications, intelligent chatbots, or agentic systems involving a RAG component, this webinar will provide you with actionable insights to take your LLM applications to the next level. Watch Apoorva Joshi, Senior Developer Advocate at MongoDB, and Maria Khalusova, Staff Developer Advocate at Unstructured where they will show you how to leverage Unstructured.io to build a data processing pipeline to chunk, embed, and extract rich metadata from raw documents. You will also learn how to use MongoDB Atlas Vector Search and MongoDB’s Aggregation framework to seamlessly combine the extracted metadata with embeddings to improve the retrieval quality and relevance of semantic search. Finally, you will learn how to orchestrate an agentic RAG system with a self-querying retriever using LangGraph.