MotherDuck Raises $47.5 Million to Make Analytics Fun, Frictionless and Ducking Awesome

Founded on Shared Beliefs

The MotherDuck team includes engineers, designers and leaders from the most innovative companies in data including Google BigQuery, Snowflake, Databricks, AWS, Meta, Elastic, Firebolt, SingleStore and more.

Jordan Tigani, Chief Duck Herder, brought together the founding team based on a shared set of beliefs formed after many years working on data infrastructure. We’ve discovered that we were building technologies that were disconnected with the needs of real-world users, especially as hardware has advanced. In the coming weeks and months, we’ll share more about these beliefs and how they led us to create MotherDuck.

Partnering with DuckDB Labs

DuckDB is the brainchild of Dr. Mark Raasveldt & Dr. Hannes Mühleisen based on their research at CWI, the Dutch national research institute for mathematics and computer science. It’s highly performant, focused on analytics and is architected as an in-process database, so it runs anywhere. DuckDB has a vibrant open source community and is seeing rapid adoption across data scientists, data analysts and data engineers.

Due in part to a clean, modern code base, the DuckDB community has demonstrated the ability to rapidly implement cutting-edge academic research. Through the DuckDB Labs partnership with MotherDuck, they can continue this innovation while also benefiting from the growth in adoption that a serverless analytics platform based on DuckDB will bring.

“DuckDB has been fortunate to have hundreds of contributors around the world. We look forward to the continued growth and adoption that partnering with MotherDuck will bring. Thanks to the MotherDuck team, we are able to focus our efforts on independent innovation of the DuckDB core platform and growth of the open source community.” Dr. Hannes Mühleisen, co-creator of DuckDB.

Long Live Easy Data

The fact is, ‘Big Data’ is dead; the simplicity and the ease of making sense of your data is a lot more important than size. Cloud data vendors are focused on performance of 100TB queries, which is not only irrelevant for the vast majority of users, but also distracts from the ability to deliver a great user experience.

Distributed architectures were once necessary to process many analytics workloads. That’s why several of us built Google BigQuery - distributing queries to hundreds or thousands of machines was the only way to achieve adequate performance. This is no longer true. Using what is essentially commodity hardware available at cloud providers, you can process large datasets with hundreds of CPU cores and terabytes of memory.

It’s time to get back to what users need: easy access to query all their data quickly, with few barriers to entry and a personalized, delightful user experience.. We’re building a serverless data analytics platform that grows with you, without the complexities of distributed computation. You can scale up and scale down with ease as your needs change.

Your Laptop is Faster than your Data Warehouse

Most users get only a small slice of time from their data warehouse. Meanwhile, previous-generation Apple laptops have 10 cores and 32GB of memory. These machines are essentially supercomputers, yet many sit idle 85% of the time because they’re each relegated to handling a few Chrome tabs.

Due to the efficient columnar-vectorized execution in DuckDB, this same laptop can run an aggregation on a billion row table in less than a second.

We’d like to enable you to take advantage of this local compute power and use it in concert with the cloud.

Let’s Challenge the Status Quo

We helped create the status quo, and now believe it’s time to challenge it. Keep an eye out on this blog, follow us on our Twitter and subscribe to our e-mail list to stay up to date as we progress towards making analytics fun, frictionless and ducking awesome.