MongoDB brings columnstore indexing to the document database • The Register

MongoDB, the company behind the document store database, has unveiled column store indexing designed to help developers create analytical queries in their applications.

Slated for preview later this year, the feature is designed to allow developers to create a purpose-built index to speed up analytical queries without requiring changes to document structure or having to move data to another system.

Sahir Azam, Product Director of MongoDB, said The register the functionality would be available in the database and Atlas DBaaS to support human-like decision making in the application based on live data.

This could be useful for developers building applications in supply chain, financial services (fraud detection) or e-commerce, he said.

“All of these aggregate multiple disparate sets of information to automate a process. What we’ve done is take synthetic and real-world client workloads and run them through the implementation we’re building right now to have a idea of ​​performance.

“This capability is a game-changer in terms of in-database performance for these types of queries. With our test suites, we see query improvement ranging from 5x to 200x for this type of complex analytical queries. of use that were never possible before.”

MongoDB’s argument is that analytics nodes can now be scaled separately, allowing teams to independently tune the performance of their operational and analytical queries without over- or under-provisioning.

Meanwhile, the company is introducing Search Facets to help developers create in-database search experiences.

Azam said, “What we’ve seen is that customers are building these sophisticated modern applications more and more, especially if they’re building them in the public cloud, you know, AWS or Azure, etc., the complexity of the underlying data architecture has really become, frankly, unmanageable.”

Atlas Search, available in the DBaaS system, is designed to help developers avoid using Elasticsearch or Solr Search outside of the main database.

“You can sort things by color or by gender or by size or by category,” Azam said. “We want to be able to serve those rich interaction experiences and it removes the complexity of having a dedicated search engine side-by-side with a MongoDB.”

Last year MongoDB acquired encryption specialist Aroki Systems and the merged technology is set to be previewed in MongoDB 6.0. Searchable encryption allows data to remain encrypted on the database, including in memory and in the CPU, while keys never leave the application and cannot be accessed by the database server. This is “an industry first for any type of database technology,” Azam said.

MongoDB drew criticism for only releasing its 5.1 database as a managed service when bugs in 5.0 had still not been fixed, and questions were asked about its commitment to the software open-source.

Azam said the company’s response has been consistent. “I think 99.9% of the world thinks about value building on the best capabilities you get at the best value and the best development experience. The licensing aspects are, frankly, something that doesn’t hasn’t really been a headwind to our business.” ®

Maria H. Underwood