MongoDB Atlas Stream Processing is finally here

Posted by Richy George on 2 May, 2024

This post was originally published on this site

MongoDB has made Atlas Stream Processing, a new capability it trailed last June, generally available, it announced at its MongoDB.local event in New York City.

It added  Atlas Stream processing to its NoSQL Atlas database-as-a-service (DBaaS) in order to help enterprises manage real-time streaming data from multiple sources in a single interface.

The new interface that can process any kind of data and has a flexible data model, bypassing the need for developers to use multiple specialized programming languages, libraries, application programming interfaces (APIs), and drivers, while avoiding the complexity of using these multiple tools, the company said, adding that it can work with both streaming and historical data using the document model.

Atlas Search Nodes is also generally available on AWS and Google Cloud, although the capability is still in preview on Microsoft Azure. This too was showcased last year: It’s a new capability inside the Atlas database that isolates search workloads from database workloads in order to maintain database and search performance.

Users will have to wait for one new capability: Atlas Edge Server. This feature, now in preview, gives developers the capability to deploy and operate distributed applications in the cloud and at the edge, the company said. It provides a local instance of MongoDB with a synchronization server that runs on local or remote infrastructure and significantly reduces the complexity and risk involved in managing applications in edge environments, allowing applications to access operational data even with intermittent connections to the cloud.

One other MongoDB feature also entered general availability: its Vector Search integration with AWS’ generative AI service, Amazon Bedrock. This means that enterprises can use the integration to customize foundation large language models with real-time operational data by converting it into vector embeddings.

Further, enterprises can also use Agents for Amazon Bedrock for retrieval-augmented generation (RAG), the company said.