Introducing Our Integrations Gallery

So you can easily find your favorite data source or tool in Cube's integrations.

Cover of the 'Introducing Our Integrations Gallery' blog post

At Cube, we're on a mission to provide developers with an analytical data access layer to help them build modern applications. We call this data access layer a ’headless BI’ platform.

The goal of headless BI is to facilitate consistent, performant, and secure access to all of your data. Of course, this mission only works if we—that is, Cube, the headless BI platform—can simultaneously support all of your data sources and make those data sources compatible with the broadest array of downstream tools possible.

So today, we’re proud to launch our new integrations page—so that you can find and read all about how your favorite tools integrate with Cube (and in that, the rest of your stack.)

The inspiration: complexity

Cube was borne out of the sheer complexity of the modern data stack—one that exists not only because of the fractal-like explosion of data sources (cloud data warehouses, transactional databases, streams, document databases, query engines, etc.) but also in the types of tools with which users consume data.

Yes, for better or worse, gone are the days of an organization simply choosing a single business intelligence tool and connecting it to a transactional database.

Now, users expect to gain insights from their data with both visualization and business intelligence tools, and with notebooks, and by building their own applications with low-code tools, powerful front-end frameworks, and charting libraries. And naturally, this expectation and the remarkable number of options available result in incredible building ability—but potentially mind-boggling connectivity complexity.

The goal: universal compatibility

Universal compatibility—meaning the ability of every data source to connect to every downstream use case—is a tall order. The good news? We have an exceptionally well-known, durable, and scalable language on our side: SQL. Cube’s Postgres-compliant SQL API is the magic translation layer by which we’re able to make universal compatibility happen.

So, perhaps your business intelligence tool doesn’t have a native driver for your fancy new analytical query engine. Well, now there’s a solution for that: if you connect your query engine to Cube, Cube’s SQL API can expose it to whichever downstream, SQL-speaking tools you choose with a simple Postgres connection.

Or, let’s take another scenario: what if you were building a customer-facing analytics application? In that case, maybe you’d prefer to expose connections to your data sources as a REST or a GraphQL API? Cube could do that too. A rigid out-of-the-box business intelligence tool just can’t offer the same flexibility as Cube, with which you could then use any number of front-end frameworks or low-code tool builders.

The future: new data sources, new tools, and much (much) more.

We believe that you should be able to curate your stack with any data source and downstream tools you want.

And we believe in open standards and in the power of a broad ecosystem.

These tightly held values mean that if you’ve come across a fantastic tool for which we haven’t yet listed an integration, we’d love to hear from you. Because really—we built this tool with a dedication to the data community and are determined to hone it further for the community (you can also find us on Slack and Github.)

Even with all of the integrations we’ve built out already, this is just the beginning of our plans for the Cube ecosystem. So looking ahead, we’ll continue adding more data sources, more downstream tools, and more categories within the modern data stack.

We’re on an exciting journey, here—and we hope you’ll join us for the ride :)

Share this article