With $21.8 million in financing, Tobiko wants to build a modern data platform

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Starting up data transformation Tobiko may not be a household name yet, but you may have seen co-founder and CEO Tyson Mao about “Beauty and the Geek” back in the aughts and its co-founder, brother and CTO Toby Mao, on the speedcubing circuit. (Both have set world records in the past, and Tyson co-founded the World Cube Association.) Since then, the brothers, along with their co-founder Iaroslav Zeigerman worked at a wide variety of companies ranging from Apple to Airbnb, Google and Netflix, where Tyson and Zeigerman first met.

Now they want to reimagine how teams work with data with Tobiko dbt compatible data transformation platform, with the popular SQLMesh And SQLGlot open source projects at its core and an intuitive low-code user interface to build data pipelines and transformations.

The company is launching its cloud platform on Tuesday, announcing a total of $21.8 million in funding, split between a $4.5 million seed round and a $17.3 million Series A round led by Theory Ventures. 20Sales, Fivetran CEO George Fraser, Census CEO Boris Jabes and MotherDuck CEO Jordan Tigani also invested in the company.

While working at Airbnb, Toby ran the company Minerva project, the company’s semantic layer for internal metrics. However, as he worked on it, he realized that Minerva’s real power was not in its semantics, but in its data transformation capabilities.

“The steps from raw data to actual business value: there’s a lot to it,” he told me. “It’s very hard work. And so ultimately we wanted to build a semantics company, but first we want to solve the transformation. And so at Airbnb I got a demo of the industry standard tools, dbt, and that gave me the inspiration to start doing this.”

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Image credits: Tobiko

Toby recognized the popularity and functionality of dbt, which has become somewhat of an industry standard for construction. But he argued that this is not the right solution for every company. “DBT is actually designed to accelerate the data stacks of Series A companies,” he said. “We wanted to create a data platform, a data transformation tool, that could work at any business, even FAANG style. So we took our experience, our collective knowledge, and built a system that can scale with large amounts of data as well as large amounts of people.”

As Zeigerman explained, at the heart of this modern platform is SQLMesh, an open-source tool that allows developers to build data pipelines with built-in tools for data transformation, testing, and collaboration. The semantic background of the team also comes to the fore here. “SQLMesh understands SQL, rather than treating it as a piece of text,” he explained. And that insight comes from SQLGlot, which Toby created during his time at Airbnb. “This ability to understand SQL unlocks a lot of things that significantly increase the speed of development and engineering productivity.”

tobiko
Image credits: Tobiko

This tool allowed Tobiko to perform syntax checking on, for example, SQL queries before sending them to the database. It also categorizes and tracks any changes engineers make in the development process and tells them if they are breaking something in relation to other data sets and transformations in the system.

“We really believe this will be one of the first observability tools that understands not only that something has broken, but why it has broken. Because we understand your code, we understand every version of every code you’ve ever written, and we can tie every failure to that change,” Tyson said.

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Image credits: Tobiko

Tobiko also offers companies the ability to create what the team calls “virtual data environments” that developers can use during the development phase and then reuse on other projects (or even in production).

The team tells me that it currently focuses primarily on data engineering teams and works with clients of all sizes, including some unicorn startups. Many of them are bringing entirely new applications to the service, but because it is compatible with dbt, there are also a number of dbt users who have made the switch.

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