MongoDB is releasing MongoDB 8.0, offering significant performance improvements, reduced scaling costs, and additional scalability, resilience, and data security capabilities.
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 32% better throughput, 56% faster bulk writes, and 20% faster concurrent writes during data replication, according to the company.
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. Queryable Encryption now supports range queries, ensuring data security while enabling powerful analytics.
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.
The 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.
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 already being rolled out to all Atlas customers, who should start seeing benefits immediately, the company said.
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.
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, according to the vendor.
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 can 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.
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.
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.
For more information about this news, visit www.mongodb.com.