Attending AWS re:Invent 2025? Check out our lightning talks at MongoDB Booth #822! Join sessions on a range of topics from MongoDB experts and partners. At specified sessions, you'll even have the opportunity to earn MongoDB Skill Badges!
When you attend a lightning session, you'll have the chance to win a MongoDB Snuggie.
Join us for an interactive session that earns you the MongoDB Overview Skill Badge and shows how MongoDB helps you build modern applications. In this architectural overview, you’ll learn how MongoDB’s flexible schema helps teams launch quickly and adapt as requirements evolve. We’ll also cover the core mechanics of replication and sharding. Features that make it possible to scale applications and maintain high availability. Together, these capabilities explain why MongoDB is trusted for data-intensive workloads and modern AI use cases.
By the end of the session, you’ll understand MongoDB’s key building blocks and walk away with a Skill Badge you can showcase on your professional networks.
Thinking Beyond Time: Fusing Long-Term and Short-Term Memory with MongoDB Atlas and Bedrock AgentCore
How do you make AI agents truly remember?
In this session, we’ll explore how MongoDB Atlas and Amazon Bedrock’s AgentCore can work together to enable both long-term and short-term memory for real-time intelligent agents. The demo shows how context-aware agents dynamically retrieve, reason, and evolve knowledge—combining vector-based recall (long-term memory in MongoDB Atlas) with transient reasoning buffers (short-term Bedrock sessions). Attendees will learn how this hybrid memory design powers personalized assistants, operational copilots, and adaptive retrieval systems capable of “thinking across time."
Real-world data is rarely flat or simple. This session uses Claude Code usage data as a practical example to explore how MongoDB’s AI-powered Developer Tools accelerates working with deeply nested, complex document structures, turning natural language into sophisticated MQL queries and aggregation pipelines.
What You'll Learn
Navigate and query heavily nested document structures using AI in MongoDB’s developer tools.
Transform natural language questions into complex aggregation pipelines without memorizing syntax
Build multi-stage pipelines that unwind arrays, traverse nested objects, and reshape complex data structures
See real examples using Claude Code data with its nested sessions, interactions, and token metrics
Key Takeaways
Discover how MongoDB’s developer tools eliminate the friction of working with complex data models. Through practical examples with Claude Code usage data, you'll see how to go from ""show me total costs by project last month"" to a working aggregation pipeline in seconds. Perfect for anyone dealing with nested JSON, API responses, or complex domain models.
Target Audience: Developers working with complex, nested data structures in MongoDB
Prerequisites: Basic JSON knowledge; no MQL or aggregation framework expertise required.
Join us for an interactive session that earns you the MongoDB Overview Skill Badge and shows how MongoDB helps you build modern applications. In this architectural overview, you’ll learn how MongoDB’s flexible schema helps teams launch quickly and adapt as requirements evolve. We’ll also cover the core mechanics of replication and sharding. Features that make it possible to scale applications and maintain high availability. Together, these capabilities explain why MongoDB is trusted for data-intensive workloads and modern AI use cases.
By the end of the session, you’ll understand MongoDB’s key building blocks and walk away with a Skill Badge you can showcase on your professional networks.
Join us for an interactive session that earns you the MongoDB Overview Skill Badge and shows how MongoDB helps you build modern applications. In this architectural overview, you’ll learn how MongoDB’s flexible schema helps teams launch quickly and adapt as requirements evolve. We’ll also cover the core mechanics of replication and sharding. Features that make it possible to scale applications and maintain high availability. Together, these capabilities explain why MongoDB is trusted for data-intensive workloads and modern AI use cases.
By the end of the session, you’ll understand MongoDB’s key building blocks and walk away with a Skill Badge you can showcase on your professional networks.
Join us for an interactive session that earns you the MongoDB Overview Skill Badge and shows how MongoDB helps you build modern applications. In this architectural overview, you’ll learn how MongoDB’s flexible schema helps teams launch quickly and adapt as requirements evolve. We’ll also cover the core mechanics of replication and sharding. Features that make it possible to scale applications and maintain high availability. Together, these capabilities explain why MongoDB is trusted for data-intensive workloads and modern AI use cases.
By the end of the session, you’ll understand MongoDB’s key building blocks and walk away with a Skill Badge you can showcase on your professional networks.
Enterprises are racing to harness the power of AI while ensuring security, compliance, and efficiency at scale. In this session, discover how MongoDB and IBM LinuxONE collaborate to build a trusted, resilient Data & AI platform for large financial services institutes. Whether you’re modernizing legacy systems or building next-gen AI applications, learn how IBM and MongoDB enable enterprise-grade elasticity, security, and performance—unlocking new value for your data and driving competitive advantage.
Discover a robust, baseline architecture for developing modern, offline-first mobile applications. This session explores how to leverage the power of AWS Amplify and AppSync alongside MongoDB Atlas. Attendees will see a practical implementation using TanStack/SQLite for local data persistence and offline-first functionality, with AppSync providing reliable, real-time updates to multiple subscribers. Learn how Atlas Stream Processing ensures seamless, low-latency data synchronization from your MongoDB cluster to AppSync, forming a highly scalable and resilient solution.
Join us for an interactive session that earns you the MongoDB Overview Skill Badge and shows how MongoDB helps you build modern applications. In this architectural overview, you’ll learn how MongoDB’s flexible schema helps teams launch quickly and adapt as requirements evolve. We’ll also cover the core mechanics of replication and sharding. Features that make it possible to scale applications and maintain high availability. Together, these capabilities explain why MongoDB is trusted for data-intensive workloads and modern AI use cases.
By the end of the session, you’ll understand MongoDB’s key building blocks and walk away with a Skill Badge you can showcase on your professional networks.
Join us for a hands-on session on semantic search with MongoDB Atlas Vector Search, where you'll learn how vector embeddings enhance search relevance by capturing meaning and context. We’ll walk through the key steps—generating embeddings with machine learning models, storing them in MongoDB, building an HNSW index, and performing queries using the $vectorSearch aggregation stage. You'll also explore similarity metrics like Euclidean, cosine, and dot product, along with pre-filtering techniques to refine results.
By the end of the session, you’ll understand how to implement semantic search in your applications and earn a MongoDB Skill Badge to showcase your expertise on professional networks.
Modern chatbots fall short when they forget user context. In this lightning talk, we’ll show how to wire Anthropic Claude (via AWS Bedrock) to MongoDB Atlas so your agent can “remember” past interactions and deliver personalized, context-aware responses—without managing servers. We’ll provision services through the AWS and Atlas consoles, store/retrieve conversation state with Atlas, and enforce secure access patterns.
Discover a robust, baseline architecture for developing modern, offline-first mobile applications. This session explores how to leverage the power of AWS Amplify and AppSync alongside MongoDB Atlas. Attendees will see a practical implementation using TanStack/SQLite for local data persistence and offline-first functionality, with AppSync providing reliable, real-time updates to multiple subscribers. Learn how Atlas Stream Processing ensures seamless, low-latency data synchronization from your MongoDB cluster to AppSync, forming a highly scalable and resilient solution.
Join us for a hands-on session on semantic search with MongoDB Atlas Vector Search, where you'll learn how vector embeddings enhance search relevance by capturing meaning and context. We’ll walk through the key steps—generating embeddings with machine learning models, storing them in MongoDB, building an HNSW index, and performing queries using the $vectorSearch aggregation stage. You'll also explore similarity metrics like Euclidean, cosine, and dot product, along with pre-filtering techniques to refine results.
By the end of the session, you’ll understand how to implement semantic search in your applications and earn a MongoDB Skill Badge to showcase your expertise on professional networks.
Join us for a hands-on session on semantic search with MongoDB Atlas Vector Search, where you'll learn how vector embeddings enhance search relevance by capturing meaning and context. We’ll walk through the key steps—generating embeddings with machine learning models, storing them in MongoDB, building an HNSW index, and performing queries using the $vectorSearch aggregation stage. You'll also explore similarity metrics like Euclidean, cosine, and dot product, along with pre-filtering techniques to refine results.
By the end of the session, you’ll understand how to implement semantic search in your applications and earn a MongoDB Skill Badge to showcase your expertise on professional networks.
Thinking Beyond Time: Fusing Long-Term and Short-Term Memory with MongoDB Atlas and Bedrock AgentCore
How do you make AI agents truly remember?
In this session, we’ll explore how MongoDB Atlas and Amazon Bedrock’s AgentCore can work together to enable both long-term and short-term memory for real-time intelligent agents. The demo shows how context-aware agents dynamically retrieve, reason, and evolve knowledge—combining vector-based recall (long-term memory in MongoDB Atlas) with transient reasoning buffers (short-term Bedrock sessions). Attendees will learn how this hybrid memory design powers personalized assistants, operational copilots, and adaptive retrieval systems capable of “thinking across time."
Every MongoDB cluster shouldn't require a DevOps expert. This session demonstrates MongoDB's new Terraform Clusters module that transforms Atlas deployment from hundreds of configuration points into production-ready patterns. See how the same module that deploys your first cluster scales effortlessly to manage dozens across regions, environments, and teams.
What You'll Learn
- Get started with Terraform and Atlas in minutes using official module that handle replica specs, sharding, and auto-scaling
- Deploy your first production cluster without memorizing Atlas configuration.
- Scale from 1 to 50 clusters using the same module, with live examples managing dozens of workloads across multiple environments
Key Takeaways
Experience how MongoDB's Terraform strategy deletes complexity from 90% of use cases. Through live demos, you'll see how one module eliminates thousands of lines of boilerplate code, handles edge cases you haven't thought of yet, and accommodates new Atlas innovations like disaggregated storage without breaking existing deployments. Walk away with working patterns tailored to your maturity level from opinionated boilerplates to enterprise scale.
Target Audience: Platform engineers, DevOps teams, and developers managing MongoDB infrastructure
Prerequisites: Basic Terraform awareness
Join us for a hands-on session on semantic search with MongoDB Atlas Vector Search, where you'll learn how vector embeddings enhance search relevance by capturing meaning and context. We’ll walk through the key steps—generating embeddings with machine learning models, storing them in MongoDB, building an HNSW index, and performing queries using the $vectorSearch aggregation stage. You'll also explore similarity metrics like Euclidean, cosine, and dot product, along with pre-filtering techniques to refine results.
By the end of the session, you’ll understand how to implement semantic search in your applications and earn a MongoDB Skill Badge to showcase your expertise on professional networks.
Join us for an insightful session on advanced schema design patterns in MongoDB, where you'll learn how to optimize data models for high-performance applications. We’ll cover key patterns like Single Collection, Subset, Bucket, and Outlier, and explore how they impact query performance—especially within sharded clusters.
By the end of the session, you’ll gain practical skills to design efficient schemas for scalable systems and earn a MongoDB Skill Badge to highlight your expertise on professional networks.
Real-world data is rarely flat or simple. This session uses Claude Code usage data as a practical example to explore how MongoDB’s AI-powered Developer Tools accelerates working with deeply nested, complex document structures, turning natural language into sophisticated MQL queries and aggregation pipelines.
What You'll Learn
- Navigate and query heavily nested document structures using AI in MongoDB’s developer tools.
- Transform natural language questions into complex aggregation pipelines without memorizing syntax
- Build multi-stage pipelines that unwind arrays, traverse nested objects, and reshape complex data structures
- See real examples using Claude Code data with its nested sessions, interactions, and token metrics
Key Takeaways
Discover how MongoDB’s developer tools eliminate the friction of working with complex data models. Through practical examples with Claude Code usage data, you'll see how to go from "show me total costs by project last month" to a working aggregation pipeline in seconds. Perfect for anyone dealing with nested JSON, API responses, or complex domain models.
Target Audience: Developers working with complex, nested data structures in MongoDB
Prerequisites: Basic JSON knowledge; no MQL or aggregation framework expertise required.
Thinking Beyond Time: Fusing Long-Term and Short-Term Memory with MongoDB Atlas and Bedrock AgentCore
How do you make AI agents truly remember?
In this session, we’ll explore how MongoDB Atlas and Amazon Bedrock’s AgentCore can work together to enable both long-term and short-term memory for real-time intelligent agents. The demo shows how context-aware agents dynamically retrieve, reason, and evolve knowledge—combining vector-based recall (long-term memory in MongoDB Atlas) with transient reasoning buffers (short-term Bedrock sessions). Attendees will learn how this hybrid memory design powers personalized assistants, operational copilots, and adaptive retrieval systems capable of “thinking across time."
Modern chatbots fall short when they forget user context. In this lightning talk, we’ll show how to wire Anthropic Claude (via AWS Bedrock) to MongoDB Atlas so your agent can “remember” past interactions and deliver personalized, context-aware responses—without managing servers. We’ll provision services through the AWS and Atlas consoles, store/retrieve conversation state with Atlas, and enforce secure access patterns.
Join us for an insightful session on advanced schema design patterns in MongoDB, where you'll learn how to optimize data models for high-performance applications. We’ll cover key patterns like Single Collection, Subset, Bucket, and Outlier, and explore how they impact query performance—especially within sharded clusters.
By the end of the session, you’ll gain practical skills to design efficient schemas for scalable systems and earn a MongoDB Skill Badge to highlight your expertise on professional networks.
Discover a robust, baseline architecture for developing modern, offline-first mobile applications. This session explores how to leverage the power of AWS Amplify and AppSync alongside MongoDB Atlas. Attendees will see a practical implementation using TanStack/SQLite for local data persistence and offline-first functionality, with AppSync providing reliable, real-time updates to multiple subscribers. Learn how Atlas Stream Processing ensures seamless, low-latency data synchronization from your MongoDB cluster to AppSync, forming a highly scalable and resilient solution.
Join us for an insightful session on advanced schema design patterns in MongoDB, where you'll learn how to optimize data models for high-performance applications. We’ll cover key patterns like Single Collection, Subset, Bucket, and Outlier, and explore how they impact query performance—especially within sharded clusters.
By the end of the session, you’ll gain practical skills to design efficient schemas for scalable systems and earn a MongoDB Skill Badge to highlight your expertise on professional networks.
