While SQL was invented for the relational model, it has been unreasonably effective for many forms of data, including document data with type heterogeneity, nesting, and no schema. Couchbase Capella has both operational and analytical engines. Both the operational and analytical engines support JSON for data modeling and SQL++ for querying. As operational and analytical use cases have different workload requirements, Couchbase’s two engines have different capabilities that are tailored to address each workload’s requirements. This article highlights some of the new features and capabilities of Couchbase’s new analytical service, the Capella Columnar service.

To improve real-time data processing, Couchbase has introduced the Capella Columnar service. There are many differentiating technologies in this new service, including column-wise storage for a schemaless data engine and its processing. In this article, we’ll give you an overview of the challenges of implementing column-wise storage for JSON and the techniques used in the Columnar service to address these challenges.