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MongoDB announces columnstore indexing for its document database

Boost to in-database analytics should help replace some human decision-making, vendor claims

MongoDB, the company behind the document store database, has unveiled columnstore indexing designed to help developers build analytical queries into their applications.

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

MongoDB chief product officer Sahir Azam told The Register the feature would be available in the database and Atlas DBaaS to support human-like decision making inside the application based on live data.

It might be useful for developers building applications in supply chain, financial services (fraud detection) or ecommerce, he said.

"All of these are aggregating multiple disparate sets of information to automate a process. What we have done is take both synthetic and real customer workloads and run them through the implementation that we're building right now to get a sense of the performance.

"What this capability does is change the game in terms of performance in the database for those types of queries. With our test suites, we're seeing anywhere from a 5x to a 200x query improvement for these kind of complex analytical sort of queries. It enables use cases that were never possible before."

MongoDB's pitch 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 build search experiences within the database.

Azam said: "What we've seen is as customers build more and more of these sophisticated modern apps, 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 the core 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 experiences of interaction and it remove that complexity of having a dedicated search-engine side by side with a MongoDB."

Last year, MongoDB acquired encryption specialist Aroki Systems and technology from the merger is set to preview in MongoDB 6.0. Queryable 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. It is "an industry first in any sort of database technology," Azam claimed.

MongoDB has attracted criticism for only releasing its 5.1 database as a managed service while bugs from 5.0 had still not been fixed, and questions have been asked about its commitment to open-source software.

Azam said the company's response had been consistent. "I think 99.9 percent of the world thinks about value in building on top of the best capabilities that you get at the best price-performance and the best developer experience. The licensing aspects of it are, frankly, something that have not really been a headwind to our business." ®

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