MongoDB.local London 2024: Better Applications, Faster

MongoDB
October 3, 2024 | Updated: October 25, 2024
#genAI #Vector Search #MongoDB 8.0

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.

Photo of the crowd checking out booths at MongoDB.local London 2024

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.

Photo of a coding session during the keynote at .local London 2024

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.

Photo of MongoDB Sttaff Developer Advocate for AI, Richmond Alake, running a session at .local London 2024.

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.

Photo of the MongoDB University booth at .local London 2024.

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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Top 4 Reasons to Use MongoDB 8.0

This post is also available in: Deutsch , Français , Español , Português , Italiano , 한국어 , 简体中文 . We’re excited to announce that MongoDB 8.0 —the newest version of the world’s most popular document database, used by millions of developers and more than 50,000 customers around the world—is now generally available. MongoDB 8.0 builds upon MongoDB’s industry-leading capabilities to provide significant performance improvements, reduced costs, and greater ease of use, from local deployments to globally distributed applications at enterprise scale. Developers have long loved building with MongoDB, so we've ensured that 8.0 kept the bar extremely high for developer usability. MongoDB 8.0 was also built to exceed our customers’ most stringent security, resiliency, availability, and performance requirements, and is the most impressive version of MongoDB yet. MongoDB 8.0 gives customers the strongest possible foundation for building a wide range of applications, now and in the future. Jim Scharf, Chief Technology Officer, MongoDB For MongoDB 8.0, we focused our engineering efforts around four core goals: Optimize performance for the widest variety of applications Deliver innovative encryption to unlock new use cases Reduce costs and increase scale with rapid and intuitive horizontal scaling for high availability Ensure resilience for unexpected application demand So how do these goals actually benefit teams as they build and manage applications? We’ll start by looking at why you should use MongoDB 8.0. Whether you’re a seasoned MongoDB veteran or are new to the database, MongoDB 8.0 is a great foundation for new applications and supercharging existing ones alike. Version 8.0 combines the things developers love most about MongoDB—like an intuitive and cohesive developer experience, support for a broad set of use cases, and operational ease of use—with unparalleled performance improvements. Top reasons to switch to MongoDB 8.0 1. MongoDB 8.0 is over 30% faster than before As the data applications generate and use grows, minor inefficiencies can lead to disproportionate increases in infrastructure costs. Because many customers primarily interact with businesses through their applications, poor or inconsistent application performance can lead to customer unhappiness, lost opportunities, and declines in revenue. So it’s imperative for organizations to ensure that their applications perform consistently well. MongoDB 8.0 significantly improves performance by allowing applications to rapidly and efficiently query and transform data, with up to 36% better throughput. Architectural optimizations in MongoDB 8.0 have reduced memory usage and query times, and a combination of more efficient batch processing and optimizations has enabled 59% higher throughput for updates and 20% faster concurrent writes during data replication. Additionally, optimizations in MongoDB 8.0 mean the database can handle higher volumes of time series data and perform operations over 200% faster—with lower resource usage and costs. 2. MongoDB 8.0 is more secure than ever Data protection and security are essential. With the increasing complexity and volume of data being transmitted, stored, and processed across environments, safeguarding sensitive information with robust encryption is more critical than ever. Organizations must protect their data throughout its lifecycle—in transit over networks, at rest where it is stored, and while it’s in use for querying and processing. However, it can be challenging to encrypt data while it is queried and processed, leaving data vulnerable to exposure or exfiltration by malicious actors. MongoDB Queryable Encryption is an industry-first innovation developed by the MongoDB Cryptography Research Group. It allows customers to encrypt sensitive data on the client side, store it securely as fully randomized encrypted data in the MongoDB database, and to run expressive queries on the encrypted data for processing. MongoDB 8.0 now includes support for range queries—in addition to equality queries—to expand secure data retrieval with greater flexibility for common searches. With Queryable Encryption, the required data remains encrypted until it reaches an authorized end user using a customer-controlled decryption key—with no cryptography expertise required. 3. MongoDB 8.0 makes it cheaper and easier to scale As organizations grow, their applications’ requirements tend to evolve. For example, scaling to support millions of users can be challenging for organizations that originally designed their applications for thousands of users. This is because implementing architectural changes in production applications can involve significant effort that can be costly and time-consuming. With MongoDB 8.0, horizontal scaling is now faster and easier, and at a lower cost. With horizontal scaling, applications can scale beyond the limits of traditional database resources by splitting data across multiple servers known as shards—without having to pre-provision increasing amounts of compute resources for a single server. New sharding capabilities in MongoDB 8.0 distribute data across shards up to 50 times faster and at up to 50% lower cost to get started. 4. MongoDB 8.0 gives you more control to help your applications run smoothly End-users expect consistent application experiences, even during periods of high demand and usage spikes. Organizations without a highly durable operational database risk poor customer experiences, with lagging application behavior (or even downtime) during times of high demand. MongoDB 8.0 provides greater control for teams optimizing database performance for unpredictable spikes in usage and sustained periods of high demand. MongoDB 8.0 includes new capabilities to set a default maximum time limit for running queries, to reject recurring types of problematic queries, and to set query settings to persist through events like database restarts. These capabilities help deliver consistent application behavior and high performance, irrespective of demand spikes or unexpected events. Ready to try MongoDB 8.0? If you are building a new application, the easiest way to get started with MongoDB 8.0 is by going to mongodb.com/try , where you can sign up for a free Atlas account, download the Community edition, and learn more about self-managing MongoDB with an Enterprise Advanced subscription. If you are running a previous version of MongoDB, there are helpful upgrade tutorials for MongoDB Atlas and self-managed deployments . Additionally, documentation and expert help from the MongoDB professional services team are on hand. If you have an existing application that is not currently using MongoDB as the database, check out the MongoDB Relational Migrator tool . Relational Migrator can help you map existing relational schemas to a MongoDB schema, perform data migrations, and convert existing relational queries, triggers, and stored procedures to work with MongoDB. The MongoDB engineering and product teams listened attentively to developer feedback , and MongoDB 8.0 was built with developer usability—as well as security, durability, availability, and performance—top of mind. We’re excited for you to give it a try, and are sure you’ll enjoy the performance gains and other benefits of MongoDB 8.0!

October 2, 2024

Next →

MongoDB and Partners: Building the AI Future, Together

If you’re like me, over the past year you’ve closely watched AI’s developments—and the world’s reactions to them. From infectious excitement about AI’s capabilities, to impatience with its cost and return on investment, every day has been filled with AI twists and turns. It’s been quite the roller coaster. During the ride, from time to time I’ve wondered where AI falls on the Gartner hype cycle, which gives "a view of how a technology or application will evolve over time." Have we hit the "peak of inflated expectations" only to fall into the "trough of disillusionment?" Or is the hype cycle an imperfect guide, as The Economist argues? The reality is that it takes time for any new technology—even transformative ones like AI—to take hold. And every advance, no matter how big, has had its detractors. A famous example is that of Picasso (!), who in 1968 said, “Computers are useless. They can only give you answers.” (!!) For our part, MongoDB is convinced that AI is a once-in-a-generation technology that will enhance every future application—a belief that has been reinforced by the incredible work our partners have shared at MongoDB’s 2024 events. Speeding AI development MongoDB is committed to helping organizations of all sizes succeed with AI, and one way we’re doing that is by collaborating with the MongoDB partner ecosystem to create powerful, user-friendly AI development tools and solutions. For example, Fireworks.ai —which is a member of the MongoDB AI Applications Program ecosystem —created an inference solution that hosts gen AI models and supports containerized deployments. This tool makes it easier for developers to build and deploy powerful applications with a range of easy-to-use tools and customization options. They can choose to use state-of-the-art, open-source language, image, and multimodal foundation models off the shelf, or they can customize and fine-tune models to their needs. Jointly, Fireworks.ai and MongoDB provide a solution for developers who want to leverage highly curated and optimized open-source models and combine these with their organization’s own proprietary data—and to do so with unparalleled speed and security. “MongoDB is one of the most sophisticated database providers, and it’s very easy to use,” said Benny Chen , cofounder of Fireworks.ai. "We want developers to be able to use these tools, and we want to work with providers who enable and empower developers." Nomic , another MAAP ecosystem member, also enables developers with best-in-class solutions across the entire unstructured data workflow. Their Embed offering, available through the Nomic API , allows users to vectorize large-scale datasets for use in text, image, and multimodal retrieval applications, including retrieval-augmented generation (RAG), using only their web browser. The Nomic-MongoDB solution is a highly efficient, open-weight model that developers can use to visualize the unstructured datasets they store in MongoDB Atlas . These insights help users quickly discover trends and articulate data-driven value propositions. Nomic also supported the recently announced vector quantization in MongoDB Atlas Vector Search , which reduces vector sizes while preserving performance. Last—but hardly least!—there’s our new reference architecture with MAAP partners AWS and Anthropic. Announced at MongoDB.local London , the reference architecture supports building memory-enhanced AI agents, and is designed to streamline complex processes and develop smarter, more responsive applications. For more—including a link to the code on Github— check out the MongoDB Developer Center . Making AI work for anyone and everyone The companies MongoDB partners with aren’t just making gen AI easier for developers—they’re building tools for everyone. For example, Capgemini has invested $2 billion in gen AI and is training 100,000 of its employees in the technology. GenYoda, a solution that helps insurance professionals with their daily work, is a product of this investment. GenYoda leverages MongoDB Atlas Vector Search to analyze large amounts of customer data, like policy statements, premiums, claims history, and health information. Using GenYoda, insurance professionals can quickly analyze underwriters’ reports to make informed decisions, create longitudinal health summaries, and streamline customer interactions to improve contact center efficiency. GenYoda can ingest 100,000 documents in just a few hours and respond to users’ queries in two to three seconds—a metric on par with the most widely used gen AI models. And it produces results: in one example, by using Capgemini’s solution an insurer was able to increase productivity by 15%, add new reports 25% faster (thus speeding decision-making), and reduce the manual effort of searching PDFs, increasing efficiency by 10%. Building the future of AI together So, what’s next? Honestly, I’m as curious as you are. But I’m also incredibly excited. At MongoDB, we’re active participants in the AI revolution, working to embrace the possibilities that lie ahead. The future of gen AI is bright, and I can’t wait to see what we’ll build together. To learn more about how MongoDB can accelerate your AI journey, explore the MongoDB AI Applications Program .

November 4, 2024