MotherDuck

“On top of compute-heavy warehouses, agent-driven queries would create a serious cost problem. MotherDuck’s architecture is an excellent fit for the kind of exploration and unpredictable queries that agents need to be useful.”

“Every meeting now is shifted from trying to find answers to what to do about them. Users are able to make a Dive or chat with MotherDuck through Claude, find new design issues, and ask: what should we do about it?”

“We’re scaling rapidly, but our Postgres cluster kept falling over on analytical workloads, even after throwing hardware at it. With AI labs and Fortune 100 customers depending on us, that wasn’t an option. Migrating to MotherDuck made our heaviest queries 30x faster, and it is now the source-of-truth for our core analytical workloads.”

“Agent-driven queries would create a serious cost problem on compute-heavy warehouses. MotherDuck’s architecture is an excellent fit for the kind of exploration agents need.”

“With MotherDuck, we're seeing that response is just a lot snappier. We can see that we're just going deeper because we have more time to spend on the data.”

“I've been doing this for five months now," Stan says. "And I can now, with fair confidence, go in and get questions answered. The remarkable thing is that I don't have to know anymore where things are. Claude can find things.”

“It's turned laborious and boring tasks into fun. I mean, that's as clear as I can state it.”

“It's been transformative for the company.”

“I didn't have to worry about accidentally costing the company a lot of money with my side data projects. And I could feel pretty comfortable that it would be able to serve my team for their needs.”

“We save tens of thousands of dollars each month by not doing that transformation. Users want to see their query results in around seven seconds or less. As long as you can hit that, you can avoid any extra costs. MotherDuck allowed us to fit well within those seven seconds without doing all those expensive transformations.”

“Because of MotherDuck's serverless model, we can scale up certain customers without scaling an entire cluster. We got a better customer experience without taking a big hit upgrading our entire stack.”

“Having that MCP server will allow them to dig into the data and answer questions for themselves without having to write SQL queries or really fully understand how SQL works.”

“The support from the MotherDuck team has been really valuable. I definitely haven't gotten that level of support with cloud data warehouses I've used in the past. I heavily used Snowflake at previous jobs and the support definitely wasn't as responsive or as knowledgeable with addressing issues.”

“MotherDuck is great with the service accounts. There is no login for a service account. It's just a token. Tokening is just a lot simpler and a lot more secure.”

“Snowflake's role-based access control turned into a nightmare at my previous job—managing all the different user accounts, the roles tied to those user accounts, what they could do at schema, table, and database levels. Not having to do that in MotherDuck has been a total game changer.”

“The more I worked with it, the more I was just like, oh my God, this is so much simpler than working with Snowflake.”

“MotherDuck has let us just focus on the analytics and the roll up, the actual querying portion of it, and has kind of kicked out all of the concerns and time and research on where are we storing this data long term? What about the costs? What about the latency? What about the scale? All of those are sort of afterthoughts now.”

“You don't need to be a data engineer to explore ideas,” says Charles. “And when you do, you're working from the same logic, the same facts, the same raw source — not someone's interpretation of it.”

“We went from local to cloud infrastructure by changing two characters,” says Charles. “I swapped in ‘md:’ and it just worked.”

“Omni gave analysts a way to explore the system holistically — linking live models, market context, and internal signals without code, training, or handoffs,” explains Charles. “It didn’t ask us to reshape our thinking to fit the tool — it fit the way we already think.”

“MotherDuck is insanely performant, and there’s no infrastructure to manage,” says Charles. “The cost of experimentation is incredibly low — which means we can afford to ask more questions and build more features, faster.”

“MotherDuck solves all sorts of really hard problems for us so that we can just focus on building UDisc. It’s a big unlock not only for our business but also for disc golf as a sport. We’re just scratching the surface right now of what’s possible.”

“MotherDuck gives us the compute power of DuckDB, scaled up into a production-grade platform. It makes it simple to iterate while solving for the concurrent writes limitation of local DuckDB.”

“We have a lot of comfort knowing that as we level up and need to grow within our data stack, we have a solid foundation.”

“We haven't had to make the full dive to a hugely expensive BI suite yet.”