Since we launched our open source offering in 2019, Cube has helped thousands of companies consume data from any data source, organize it into consistent definitions, and use it with data applications. Developers and data engineers have used Cube to build a thriving ecosystem of embedded analytics features and custom data applications.
However, it’s always been our ambition to make Cube’s power more accessible to a greater diversity of data consumers.
To get there, data needs to be consistent and performant not just for developers—but also for analysts and general business users. This requires bringing Cube into the tools where these users already work: namely, business intelligence tools such as Tableau, Superset, and Power BI.
Today, we’re proud to announce a major milestone in our efforts. Cube’s updated SQL API makes our headless analytic platform available to users of every BI application.
Consistent data for every tool
We first launched a preview of Cube’s SQL API late last year. Since then, we’ve been hard at work responding to your thoughtful feedback and adding support for ways specific BI applications generate SQL queries. Now, it’s possible to connect any data visualization and BI application to Cube via the Postgres SQL interface.
Now, an organization can configure Cube—once—to securely access data sources, define data models, and cache queries. After that, every data consumer across an organization can securely access Cube’s definitions and materializations using vastly simplified queries.
No matter which tool a team uses, everyone in the organization will see the same data definitions. ‘Total Orders’ will mean the same thing in executives’ dashboards, marketers’ campaign reports, and the finance team’s revenue models.
By abstracting away complex queries, Cube reduces the difficulty of exploring data with collaborative data tools and notebooks.
By centrally managing access to up-stack data stores, Cube consistently defines, enforces, and audits who can access what; this eliminates the duplicated effort and inherent risks of defining access control within each downstream tool.
And by managing query-level caching and aggregate tables, Cube reduces the bandwidth costs and degraded performance of directly, repeatedly querying raw data stores.
Here comes Hydra
We’ve already talked about using Cube as a “headless” BI layer. With our SQL API, now it’s easier than ever to connect all of your “heads.”
Everything you need to connect Cube to BI tools is available from Cube’s “Overview” window. Just click “How to connect your BI tool” to reveal connection details, then connect to Cube as a PostgreSQL data source from within your BI tool.
Your cubes will be exposed as tables, where both your measures and dimensions are columns.
This makes it possible to query Cube as a data source from within your BI tool, ensuring consistent data for every data consumer.
The new SQL API is available in both the open source Cube tool and Cube Cloud, the managed Cube service hosted within select regions of the Google Cloud Platform and Amazon Web Services. You may sign up for a free Cube Cloud account at cube.dev/cloud.
Interested in getting started? See our guide to working with BI tools.
Need help? Have feedback? We love hearing from you. Join the Cube Dev Slack community or drop us a line.