MongoDB boosts its search capabilities for developers Computerworld

MongoDB’s Atlas cloud-managed database is enriched with a set of analytics and search capabilities that expand the possibilities for developers for new application use cases. The publisher also unveils with Queryable Encryption what it presents as the first encrypted search function diagram.

MongoDB shows its ambition to provide developers with a data platform that expands the variety of use cases that its document-oriented database technology supports. Two years ago, Mark Porter took charge of the engineering teams of the American publisher and when we meet the CTO, he clearly explains MongoDB’s desire to include analytical functions in the capabilities of the platform. , search and all synchronization technologies with mobiles. It is a question here of reinventing the 3rd level of three-level architectures, he explained to us during a visit to Paris (his interview will soon be published on LMI). About the annual conference MongoDB Worldwhich is being held this week in New York, a series of announcements have been made in this direction by the provider of open source solutions.

Among the new features is the Column Store Indexes feature, which will be delivered later this year. For developers, it will facilitate the integration of “in-app” analytical functions with the possibility of creating and maintaining an index built specifically for this purpose. The latter will significantly speed up many common queries without having to modify the structure of the document or having to move the data elsewhere. MongoDB explains that in addition, the analytical nodes will be able to scale separately, which will allow teams to adjust the performance of their queries separately without risking over or under-dimensioning their processing capacities. Improvements are made to time series collections in MongoDB version 6.0 with support for secondary indexes for measurements and optimizations to sort time data faster. On search functions, Atlas Search is enriched with Search Facets so that developers can quickly create richer search experiences for users.

Virtual database capabilities

On development lifecycle management, MongoDB announces capabilities to transform and move data faster in Atlas, the managed cloud version of its database. Atlas Data Lake will provide fully managed object storage capabilities that will power high performance analytical queries. It will reformat data and create partition indexes as it ingests data from Atlas databases.

In addition, Data Federation will allow teams to create virtual databases to work on data located in different sources (MongoDB clusters and storage buckets). For SQL aficionados, Atlas SQL Interface provides tools for interacting with read-only Atlas data. “This facilitates native mode queries and visualization of data in Atlas with SQL tools while preserving the flexibility of the document model”, explains the editor in a press release.

In preview, Queryable Encryption

On the deployment capabilities side, MongoDB announces the general availability of Atlas Serverless to deploy serverless functions in the three major public clouds. The publisher also unveils Queryable Encryption in preview, which it presents as the first encrypted search function schema. This makes it possible to carry out searches on data which remains encrypted at all times in the database.

Encryption keys do not leave the application and the database server cannot access them, MongoDB explains. Queryable Encryption is based on standard NIST cryptographic primitives. This functionality thus provides protection including threats coming from inside the company.

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MongoDB boosts its search capabilities for developers Computerworld

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