MongoDB updates Atlas with focus on AI & real-time applications
MongoDB, the developer data platform, has announced enhancements to MongoDB Atlas and the MongoDB Atlas Vector Search. These updated features are aimed to streamline the development of modern applications that are capable of scaling smoothly. Among these latest offerings, a new integration with Amazon Bedrock, enhancements for event-driven apps, and a new collaboration with Google Cloud to optimise Gemini Code Assist are particularly notable.
MongoDB Atlas, recognised as the most widely distributed developer data platform worldwide, is relied on by millions of developers and tens of thousands of companies worldwide to power business-critical applications across various cloud providers. The general availability of MongoDB Atlas Stream Processing will make it considerably easier to use real-time data to power responsive applications. For companies with generative AI workload requirements, the MongoDB Atlas Search Nodes are now available on Microsoft Azure, offering up to 60% faster query times and cost reduction.
Sahir Azam, Chief Product Officer at MongoDB, explained the value of these new services, stating they "not only make it easier to build, deploy, and run modern applications, but also make it easier to optimise performance while reducing costs."
MongoDB Atlas Stream Processing, now generally available, offers developers an opportunity to power event-driven applications with streaming data while MongoDB Atlas Edge Server provides a local instance of MongoDB reducing the complexity of managing data for distributed applications. MongoDB Atlas Search Nodes are also newly available for those in need of infrastructural resources dedicated to generative AI and relevance-based search workloads.
MongoDB user, John Riewerts, EVP of Engineering at Acoustic, pointed out the advantages of using Atlas Stream Processing, saying, "Our engineers can leverage the skills they already have from working with data in Atlas to process new data continuously, ensuring our customers have access to real-time customer insights."
Additionally, MongoDB has announced general availability of MongoDB Atlas Vector Search integration with Amazon Bedrock, helping to accelerate the development of engaging generative AI-powered applications. Database capabilities of MongoDB Atlas, combined with Amazon Bedrock, will enable organisations to build AI applications that can use real-time operational data to perform complex tasks securely.
MongoDB has also collaborated with Google Cloud to optimise Gemini Code Assist, aimed at helping developers accelerate application development by providing AI-powered coding assistance. Andrew Davidson, SVP of Product at MongoDB, expressed his excitement about this collaboration, stating it will "put generative AI-powered software development directly into their hands."
The enhanced collaboration between MongoDB and Google Cloud optimises Gemini Code Assist to provide developers with superior suggestions for application development on MongoDB, and is said to reduce friction throughout the whole software development and delivery process, helping programmers write high-quality code more efficiently.
