MongoDB Extends Developer Data Platform For Modern Applications

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The modern app might pop up on your smartphone and provide you with really intuitive touchscreen functions and AI-like features, but it’s only truly modern if its modernized beneath. As it is in people it is in software, it’s what’s inside that counts.

It’s also about servicing more of the data lifecycle and making it optimized for modern architectures with sophisticated levels of data encryption - all within a single integrated developer data platform.

These enhancements allow teams to accomplish more while preserving a consistent developer experience and reducing the complexity of the data infrastructure required to support modern applications. In terms of actual enhancements referenced here, MongoDB has announced a number of capabilities that make it easier for developers to build in-app analytics and power richer application experiences. As an example, column store indexing will enable users to create and maintain a purpose-built index that dramatically speeds up many common analytical queries without requiring any changes to the document structure or having to move data to another system.

“A lot has been done to extend MongoDB and Atlas to an even higher level of engineering, but we shouldn’t think of this technology as some kind of ‘kitchen sink’ solution, it’s more nuanced and sophisticated than that,” said Andrew Davidson, MongoDB VP of cloud. Among the long list of other product updates now brought forward by MongoDB is news that Atlas Data Lake will now feature fully managed storage capabilities that provide the economics of cloud object storage while optimizing for high-performing analytical queries. Atlas Data Lake reformats, creates partition indexes and partitions data as it is ingested from Atlas databases, creating a highly performant companion data lake.

 

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