We raised Series A to build headless data analytics

Less than a year ago, I was writing a blog post announcing our seed fundraising. I didn't expect to write a successor post so soon! But today we are overjoyed to announce that Cube Dev has raised $15.5M in Series A funding, led by Decibel.

It’s been a busy eleven months. Since last August, there are 5 times more servers running Cube, and as many new members in our Slack community. The past months have also seen the rollout of powerful new features including Cube Store, and the emergence of new community features and educational resources.

In announcing this funding round, I want to share what we’ve learned over that time, and explain how we will use the new funding and what we’ve learned to more quickly build the tech stack that powers data applications.

The new architecture for data applications

The database and cloud data warehouse industry is booming. We indeed have more data than ever. From the Cube community, I know a lot of seed-stage startups dealing with hundreds of millions and even billions of records.

The good news is that the technology now exists to process all of this data. Remember that less than a decade ago, only a privileged few big tech firms could afford the budget needed to run and manage Hadoop clusters on a scale, but since then, cloud data warehouses emerged as Ford's Model T for data. Now, even small companies can afford to store and analyze big data. This enables everyone to build data applications and embed intelligence into their products.

That being said, we still have to build fundamental infrastructure to make it possible—to bring data to life inside the applications. If data is the new oil, we need the tools to refine it into rocket fuel.

Developers need a new architecture to deliver data from warehouses and data lakes to applications at scale, and there are hard problems to solve in designing this architecture:

How do we abstract metrics definitions and make them consistent, testable, and version controllable?

How do we ensure that our API layer supports a large number of users and high volumes of data without growing in complexity?

How do we manage complex multi-tenancy scenarios and per-end-user custom metrics?

How do we aggregate and cache the data to process hundreds and even thousands of queries per second?

We’ve spent more than two years tackling these questions with all of you in our amazing Cube community, and we’ve all learned a lot.

Over two years ago, when Pavel and I were playing ping-pong and chatting about open-sourcing Cube.js, I couldn't have imagined where it would lead us. Today’s Cube is so different from what we initially released. Community not only contributed features but pioneered many fundamental architecture decisions we have now in the Cube.

Now, with new funding, we're excited to start a new chapter and to build more and faster.

Where we go from here

Cube’s mission is to empower developers to build data applications. To pursue this mission, here is some of what we have planned:

Hiring. We plan to build a team of 30 people by the end of the year and double our open-source engineering team. This allows us to fix bugs and ship new features faster.

Extend Cube Store. It's been less than 3 months since we released Cube Store, but it's already been adopted by more than half of Cube users. As many of you have noticed, Cube Store provides a significant boost for latency and concurrency on analytics queries like Top-K. We intend to further improve its performance and the ease of configuring and deploying Cube Store and work to make its immense power accessible to every user.

New features. I always enjoy hours spent chatting with the community about what we need to build next. There are many things I know you are excited about. Two frequent requests are real-time pre-aggregations from Kafka streams and databases, and BI connectors. I'm happy to share that we've already started to work on these, and plan to ship previews later this year. Please DM me on Slack if you are interested in running Cube on top of real-time and streaming data, or connecting Cube to your BI tool.

Launch Cube Cloud. We're also hard at work building Cube Cloud, our fully managed Cube service coming later this year too. Managing infrastructure opens so many new opportunities to build features we’ve always wanted to add to Cube but couldn’t without access to the underlying infrastructure. I can't wait to share it with you all. Cube Cloud will launch to general availability in the autumn, but first we’re working with design partners who can test Cube Cloud with their data, influence feature development, and work hands-on with the Cube Dev team in advance of general availability. Can you help? Don’t miss this opportunity to shape Cube’s next chapter. Drop us a line to learn more.