Couchbase Server 7.1 advances enterprise NoSQL database
The database vendor is updating its namesake platform with an optimized storage engine and new integrations to connect data sources including cloud data lakes.
The Couchbase Server 7.1 release was made generally available on Tuesday, providing users of the NoSQL database with new features designed to improve operational efficiency.
A week after the IPO, the vendor released Couchbase Server 7.0, bringing relational database capabilities to the platform.
With Couchbase Server 7.1, the vendor added a new storage engine to help optimize data management as well as provide support for Arm processors. The update also supports the Apache Parquet data format that is widely used in data lakes.
In an effort to support operational analytics, Couchbase has integrated a direct Tableau connector that enables Tableau users to run queries against data stored in a Couchbase database.
The updates in Couchbase 7.1, including Parquet file support, can make Couchbase more productive and useful in data lake and data lakehouse environments, said IDC analyst Carl Olofson.
"The high-density storage engine and Arm processor support offer more scalability at lower cost, which means that users can build more comprehensive solutions without spending an arm and a leg," Olofson said. "The security and availability capabilities make Couchbase a more attractive platform for enterprise data management, especially given their schema and SQL support, which offers a best of both worlds capability between document and relational databases."
NoSQL database optimizations in Couchbase Server 7.1
Ravi Mayuram, senior vice president of engineering and CTO at Couchbase, said the main piece of innovation in the 7.1 update is the new storage engine. The new engine was developed under the code name Magma and replaces the previous engine, which was known as Plasma.
The high-density storage engine and Arm processor support offer more scalability at lower cost, which means that users can build more comprehensive solutions without spending an arm and a leg.
Carl OlofsonAnalyst, IDC
With the new storage engine, Mayuram said Couchbase can store more data, with solid performance for large workloads.
Among the enhancements that enable the storage engine are a series of computer science storage approaches, including log-structured merge-tree, log-structured storage and skip lists.
The three approaches are deep storage techniques designed to enable systems to keep an efficient balance of data in memory and on disk with methods that enable fast and more optimized data access. With Magma, more frequently accessed data is put in memory, while less frequently accessed data resides on disk.
Connectivity to commodity cloud object storage is also being extended in Couchbase Server 7.1. Previous releases of Couchbase supported Amazon S3, and the update adds support for Microsoft Azure and Google Cloud Platform object storage.
"Customers can keep data in public cloud object storage and whenever they need to query that data, they can use the integration to pull the data into the database," Mayuram said.
User-defined functions land in Couchbase Server 7.1
User-defined functions are a common capability in traditional relational database platforms like open source PostgreSQL, for example.
A user-defined function enables custom functionality with a SQL query against a database. Couchbase is now bringing user-defined functions to its platform and enabling users to write functions in JavaScript.
With user-defined functions, Mayuram said users will be able to make custom functions execute as part of SQL transactions, which can be useful for operations such as data transformations to adjust schema and format.
"This is about bringing logic closer to data," he said.
