The cloud SQL analytics platform that helps you do more with your data. A unique architecture enables dual query execution across local machines and the cloud, letting you experience smooth workflows and ultra-efficient performance that won’t break the bank.
Hey folks… I’m Jordan, co-founder and chief duck-herder at MotherDuck.
I started MotherDuck with a handful of fellow database industry nerds because we were frustrated that the pace of innovation seemed to be slowing for people that work with data. More and more entries were getting added into the modern data stack, and yet it had been a while since someone had really done something new or made a huge improvement.
In the last decade, servers got orders of magnitude more powerful, laptops went from toys to mini-supercomputers, and fiber to the home and workplace became common. At the same time, those of us working with data infrastructure started noticing that data workloads weren’t really growing in size. The constraints were dissolving, bringing opportunity for change.
We built MotherDuck to help people solve problems using data. Our goal isn’t to be the biggest query engine or the fastest data warehouse. We want you to be able to go from formulating questions to understanding the answers in as few steps as possible.
We’re built on DuckDB, the open source SQL analytics engine that has gone from the database that no one has heard of to the one that everyone is talking about. Collaboration with the DuckDB team has let us build something pretty unique; the delta between running on your laptop and running in the cloud is as small as adding three characters to your database path. MotherDuck with DuckDB also enables our users to build highly-interactive data applications that save on cloud compute costs by running some of your query workload locally,
If you like ducks, and you like databases, give it a try, we’re eager to get feedback.
Congratulation's @jtigani! MotherDuck sounds like a breath of fresh air in the data management world! It's great to see a solution focused on simplifying the path from questions to answers, and the cost savings from running queries locally is a big plus.
Hey Jordan and the MotherDuck team,
Congrats on the launch! This is a game-changer for marketers like me who work with data daily. Simplifying the process from question to answer is exactly what we need.
I'm curious, how does MotherDuck handle scaling for large datasets without compromising performance?
Looking forward to giving it a try!
Best,
Emily
Your guys UI is definitely very unique and attractive. I really love the style! Congrats on the launch.
Congratulations the launch team! Can you share more about the dual query execution and how it sets your product apart from others in the market?
Glad to see some improvements for how to speed up the processes and keep innovation flowing!
Congrats on the launch 🚀
Congrats on the launch, Jordan! MotherDuck sounds like a refreshing take on data infrastructure. How seamless is the integration between local and cloud queries with DuckDB? Excited to see how this simplifies data analysis!
MotherDuck looks awesome! How does your dual query execution architecture manage data consistency and latency between local machines and the cloud?
It's exciting to see a fresh approach to data infrastructure. How do you envision MotherDuck evolving in the next few years?
Love the branding 🦆 Who is the ideal customer for this? I never ventured beyond just using regular GA4 for analytics. 😅
MotherDuck's approach to blending local and cloud queries sounds innovative! Can you share more about the collaboration with DuckDB?
MotherDuck's approach to making data work easier and faster is awesome. I love the local query feature. Can't wait to try it out!
Congrats on the launch of MotherDuck, Jordan! 🎉 Your cloud SQL analytics platform sounds like a breakthrough in the data world. The unique architecture enabling dual query execution across local machines and the cloud is a brilliant solution for achieving smooth workflows and ultra-efficient performance without breaking the bank.
