Since we kicked off MongoDB’s series of 2024 events in April, we’ve connected with thousands of customers, partners, and community members in cities around the world—from Mexico City to Mumbai. Yesterday marked the nineteenth stop of the 2024 MongoDB.local tour, and we had a blast welcoming folks across industries to MongoDB.local London, where we discussed the latest technology trends, celebrated customer innovations, and unveiled product updates that make it easier than ever for developers to build next-gen applications.
Over the past year, MongoDB’s more than 50,000 customers have been telling us that their needs are changing. They’re increasingly focused on three areas:
Helping developers build faster and more efficiently
Empowering teams to create AI-powered applications
Moving from legacy systems to modern platforms
Across these areas, there’s a common need for a solid foundation: each requires a resilient, scalable, secure, and highly performant database.
The updates we shared at MongoDB.local London reflect these priorities. MongoDB is committed to ensuring that our products are built to exceed our customers’ most stringent requirements, and that they provide the strongest possible foundation for building a wide range of applications, now and in the future.
Indeed, during yesterday’s event, Sahir Azam, MongoDB’s Chief Product Officer, discussed the foundational role data plays in his keynote address. He also shared the latest advancement from our partner ecosystem, an AI solution powered by MongoDB, Amazon Web Services, and Anthropic that makes it easier for customers to deploy gen AI customer care applications.
MongoDB 8.0: The best version of MongoDB ever
The biggest news at .local London was the general availability of MongoDB 8.0, which provides significant performance improvements, reduced scaling costs, and adds additional scalability, resilience, and data security capabilities to the world’s most popular document database.
Architectural optimizations in MongoDB 8.0 have significantly reduced memory usage and query times, and MongoDB 8.0 has more efficient batch processing capabilities than previous versions. Specifically, MongoDB 8.0 features 36% better read throughput, 56% faster bulk writes, and 20% faster concurrent writes during data replication. In addition, MongoDB 8.0 can handle higher volumes of time series data and can perform complex aggregations more than 200% faster—with lower resource usage and costs. Last (but hardly least!), Queryable Encryption now supports range queries, ensuring data security while enabling powerful analytics.
For more on MongoDB.local London’s product announcements—which are designed to accelerate application development, simplify AI innovation, and speed developer upskilling—please read on!
Accelerating application development
Improved scaling and elasticity on MongoDB Atlas capabilities
New enhancements to MongoDB Atlas’s control plane allow customers to scale clusters faster, respond to resource demands in real-time, and optimize performance—all while reducing operational costs.
First, our new granular resource provisioning and scaling features—including independent shard scaling and extended storage and IOPS on Azure—allow customers to optimize resources precisely where needed. Second, Atlas customers will experience faster cluster scaling with up to 50% quicker scaling times by scaling clusters in parallel by node type.
Finally, MongoDB Atlas users will enjoy more responsive auto-scaling, with a 5X improvement in responsiveness thanks to enhancements in our scaling algorithms and infrastructure. These enhancements are being rolled out to all Atlas customers, who should start seeing benefits immediately.
IntelliJ plugin for MongoDB
Announced in private preview, the MongoDB for IntelliJ Plugin is designed to functionally enhance the way developers work with MongoDB in IntelliJ IDEA, one of the most popular IDEs among Java developers. The plugin allows enterprise Java developers to write and test Java queries faster, receive proactive performance insights, and reduce runtime errors right in their IDE.
By enhancing the database-to-IDE integration, JetBrains and MongoDB have partnered to deliver a seamless experience for their shared user-base and unlock their potential to build modern applications faster. Sign up for the private preview here.
MongoDB Copilot Participant for VS Code (Public Preview)
Now in public preview, the new MongoDB Participant for GitHub Copilot integrates domain-specific AI capabilities directly with a chat-like experience in the MongoDB Extension for VS Code.
The participant is deeply integrated with the MongoDB extension, allowing for the generation of accurate MongoDB queries (and exporting them to application code), describing collection schemas, and answering questions with up-to-date access to MongoDB documentation without requiring the developer to leave their coding environment. These capabilities significantly reduce the need for context switching between domains, enabling developers to stay in their flow and focus on building innovative applications.
Multicluster support for the MongoDB Enterprise Kubernetes Operator
Ensure high availability, resilience, and scale for MongoDB deployments running in Kubernetes through added support for deploying MongoDB and Ops Manager across multiple Kubernetes clusters.
Users now have the ability to deploy ReplicaSets, Sharded Clusters (in public preview), and Ops Manager across local or geographically distributed Kubernetes clusters for greater deployment resilience, flexibility, and disaster recovery. This approach enables multi-site availability, resilience, and scalability within Kubernetes, capabilities that were previously only available outside of Kubernetes for MongoDB. To learn more, check out the documentation.
MongoDB Atlas Search and Vector Search are now generally available via the Atlas CLI and Docker
The local development experience for MongoDB Atlas is now generally available. Use the MongoDB Atlas CLI and Docker to build with MongoDB Atlas in your preferred local environment, and easily access features like Atlas Search and Atlas Vector Search throughout the entire software development lifecycle. The Atlas CLI provides a unified and familiar terminal-based interface that allows you to deploy and build with MongoDB Atlas in your preferred development environment, locally or in the cloud.
If you build with Docker, you can also now use Docker and Docker Compose to easily integrate Atlas in your local and continuous integration environments with the Atlas CLI. Avoid repetitive work by automating the lifecycle of your development and testing environments and focus on building application features with full-text search, AI and semantic search, and more.
Simplifying AI innovation
Reduce costs and increase scale in Atlas Vector Search
We announced vector quantization capabilities in Atlas Vector Search. By reducing memory (by up to 96%) and making vectors faster to retrieve, vector quantization allows customers to build a wide range of AI and search applications at higher scale and lower cost.
Generally available now, support for scalar quantized vector ingestion lets customers seamlessly import and work with quantized vectors from their embedding model providers of choice—directly in Atlas Vector Search. Coming soon, additional vector quantization features, including automatic quantization, will equip customers with a comprehensive toolset for building and optimizing large-scale AI and search applications in Atlas Vector Search.
Additional integrations with popular AI frameworks
Ship your next AI-powered project faster with MongoDB, no matter your framework or LLM of choice. AI technologies are advancing rapidly, making it important to build and scale performant applications quickly, and to use your preferred stack as your requirements and available technologies evolve.
MongoDB’s enhanced suite of integrations with LangChain, LlamaIndex, Microsoft Semantic Kernel, AutoGen, Haystack, Spring AI, the ChatGPT Retrieval Plugin, and more make it easier than ever to build the next generation of applications on MongoDB.
Advancing developer upskilling
New MongoDB Learning Badges
Faster to achieve and more targeted than a certification, MongoDB’s free Learning Badges show your commitment to continuous learning and to proving your knowledge about a specific topic. Follow the learning path, gain new skills, and get a digital badge to show off on LinkedIn.
Check out the two new gen AI learning badges!
Building gen AI Apps: Learn to create innovative gen AI apps with Atlas Vector Search, including retrieval-augmented generation (RAG) apps.
Deploying and Evaluating gen AI Apps: Take your apps from creation to full deployment, focusing on optimizing performance and evaluating results.
Learn more
To learn more about MongoDB’s recent product announcements and updates, check out our What’s New product announcements page and all of our blog posts about product updates. Happy building!
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