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$37 mln in a Series A: Tinybird – The Way to Build Realtime Data Products

Founded in 2019, Tinybird enables companies to ingest data from myriad sources, spanning data streams, data warehouses, data lakes, and more.

Tinybird, a platform that helps developers build products quickly on top of real-time data, has raised $37 million in a series A round of funding.

The raise comes as companies across the spectrum generate more data than ever, from mobile devices and SaaS apps, to IoT and beyond. While this abundance of data can unlock a wealth of insights, combining the data and deriving meaningful answers to real business questions in real time can be a Herculean task for all but the biggest of enterprises — which is where Tinybird comes into play.

“Large companies are generating more and more data, and they’ve invested a ton in capturing it and storing it in data warehouses,” Tinybird cofounder and CEO Jorge Gomez Sancha told VentureBeat. “But what we see is that it still takes an army of data engineers for them to take advantage of it in real time.”

Ingesting data

Founded in 2019, Tinybird enables companies to ingest data from myriad sources, spanning data streams, data warehouses, data lakes, and more. Once the data is inside Tinybird, developers can then start building products on top of that data using good, old-fashioned SQL queries and APIs (application programming interfaces).

Traditionally, companies might have had to create data pipelines powered by the myriad ETL (extract, transform, load) and similar data integration tools out there. And that may well make sense for specific use cases, such as running a report, training a machine learning model, or other ad hoc queries. But Tinybird posits that it’s just not suitable for building scalable products centered around real-time “streaming” data.

“They are simply not designed to scale to handle hundreds or thousands of queries per second, and they are not designed to exploit the data in real time, something that is becoming the cost-of-entry to compete in many industries,” Gomez Sancha said. “[And] they are not designed for developers.”

And so Tinybird does all the heavylifting for them, serving up low-latency, high-concurrency APIs to leverage the data in minutes using tools that developers are already familiar with — and without having to worry about any of the underlying infrastructure.

“You could think of Tinybird as a serverless data warehouse with tools for developers,” Gomez Sancha added. “It often sits in parallel to existing data warehouses, taking data from the same sources — and oftentimes from the data warehouses themselves — and it helps accelerate data for those use cases that require real-time response times and scale.”

So what kinds of products and features might a developer wish to spin up off the back of Tinybird? A typical example might be user-facing dashboards for in-product analytics.

“Today, it is no longer enough to provide a good service — customers want to understand how much value they are getting from it,” Gomez Sancha explained. “With Tinybird you can ingest data, such as events and transactions, and expose low-latency, scalable APIs in minutes to power those user-facing dashboards with real-time latency.”

Elsewhere, a developer might want to create customized feeds to sort products in an ecommerce application by popularity, relevance and so on. Or security teams might also want to use Tinybird for automation and events processing as part of their anomaly-detection workflow.

There are other similar companies out there in the ether, such as Imply and Rockset, while Tinybird is also encroaching into territory occupied by traditional data warehouses. But with a purely serverless approach, one that’s focused on developers, Tinybird is hoping to set itself apart.

“We are optimizing to ensure that any developer, using SQL and APIs, can start capturing data and consume it in their apps and data products in a matter of minutes,” Gomez Sancha said.