Data Analytics Startup MotherDuck Raises $52.5M To Accelerate Its Development Work
The new Series B funding round brings the Seattle company’s total funding to $100 million and boosts its valuation to $400 million.
Data analytics startup MotherDuck has raised $52.5 million in a Series B funding round that brings the Seattle-based company’s total funding to $100 million and puts its post-money valuation at $400 million.
As part of this week’s announcement MotherDuck also said it is continuing to add capabilities to the company’s data analytics platform, initially launched in June, and is now opening up trials of the cloud software to all comers.
MotherDuck also said it has expanded the roster of big data technology integrations with its platform.
MotherDuck is developing a serverless data analytics system built on DuckDB, an open-source, next-generation OLAP database. The company was founded last year by CEO Jordan Tigani, previously the chief product officer at database developer SingleStore and before that a founding engineer for Google BigQuery.
Unlike other data analysis platforms like Snowflake and Google BigQuery that focus on processing huge datasets, MotherDuck is targeting more lightweight analytics chores that many businesses face every day. The goal is to develop a data analytics platform that’s easy to use and can leverage the processing power of today’s hardware – even on laptops – without the complexities of distributed computation.
MotherDuck has been previewing its technology, but until now there has been a wait list. This week the company said it will no longer have a waitlist and anyone interested in trying the platform at scale can now do so by signing up at motherduck.com.
There are already more than 2,000 users working with the MotherDuck technology, the company said, including such use cases as a cloud data warehouse, a data lake query engine, and a serverless backend for data applications.
“We’re proud of what we’ve been able to achieve over the last year alongside the DuckDB community and the DuckDB Labs team,” Tigani said in a statement. “Our initial funding allowed us to grow our engineering team to get our platform launched and in use by almost 2,000 analysts,” he said.
Prior to this week’s funding round MotherDuck raised $12.5 million in seed funding and $35 million in a Series A funding round in November 2022.
The latest funding round was led by Felicis along with new and existing investors a16z, Madrona, Amplify Partners, Altimeter, Redpoint, Zero Prime and others. Felicis general partner Viviana Faga is joining MotherDuck’s board of directors.
“We are excited to partner with Jordan and the MotherDuck team as they build a platform designed to seamlessly blend speed and user-friendliness, thereby simplifying and making analytics widely accessible,” Faga said in a statement. “Analysts clearly need the speed of working with data at the edge, as well as the flexibility to query cloud-based data. The era of serverless data analytics is here.”
The company this week said it has added a number of “feedback-driven improvements to the [software’s] analyst experience” including faster data import, a better notebook interface with SQL auto-complete, optimized hybrid query planning and improved database sharing.
“With this funding and the momentum surrounding our platform and DuckDB’s adoption, the sky’s the limit,” Tigani said. “The key is a simplified scale-up approach to SQL analytics; for the 95 percent of us who do not have petabyte-scale data, a scale-up approach to analytics based on an engine like DuckDB can be faster, cheaper and more user-friendly than distributed architectures.”
At the initial launch in June MotherDuck announced 16 data technology integrations with its platform. This week the company unveiled 11 more including integrations with Cube, dltHub, Evidence, GoodData, Kestra, Metabase, InfinyOn, LlamaIndex, Sling, Streamlit and Voltran Data. Integration with Airbyte is also newly available to users this week and integrations with Fivetran and Tableau are underway, according to the company.