Jordan Tigani
@jrdntgn
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Co-founder / Chief Duck-herder at MotherDuck Formerly: Various roles building cloud analytics software he / him
Seattle, WA
Joined August 2014
RT @MizrahiEtai: Introducing Seda: the AI agent for data and analytics. Work with data in natural language questions in plain English—Seda….
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RT @PrateekVJoshi: To kick off the new year, I invited @jrdntgn to Infinite ML. He's the cofounder and CEO of MotherDuck. They've raised $1….
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RT @rauchg: Two novel storage solutions added to the @vercel marketplace:.▪ @niledatabase: multi-tenant serverless postgres with unlimited….
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RT @motherduck: 💥 MotherDuck's native integration is now LIVE on @vercel Marketplace 💥. Developers can now deploy MotherDuck for their Verc….
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I'm super excited about this launch. it solves one of the scalability gaps we had in MotherDuck, which was "what happens when I put up a dashboard that gets hammered?"
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Who says the only people who can build foundation models are megacorps?.
We are Perceptron AI, a new foundation model company from @ArmenAgha, @AkshatS07. Foundation models transformed the digital realm, now it’s time for the physical world. We’re building the first foundation models designed for real-time, multi-modal intelligence across the real.
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RT @akshaykagrawal: To our community: marimo wouldn't be where it is today without your help. Your code contributions and feedback shape m….
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Here is a link to the benchmark with all of the hosted platforms included:
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I don't like to make too many comparisons but we're faster than things that cost a couple of orders of magnitude more. (at this one benchmark, your mileage may vary).
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A few months ago, I wrote that the important thing about a database is how fast it is improving, not how fast it is today. Since then, MotherDuck has gotten 7x faster, according to ClickBench. We still have a lot of work to do, but not bad so far.
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RT @mattturck: Is Big Data dead?. @jrdntgn and the @motherduck and @duckdb teams are leading the “small data” movement for faster and simpl….
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Most MotherDuck queries got almost 2x faster today. One of our engineers figured out how to do dual execution in one round trip instead of 2, so I'm seeing sub 50ms queries measured from the client in NYC. (even a 🦆 can't exceed the speed of light).
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RT @marcfdupuis: This week I attended @smalldatasf . For folks who know me, you know that I’m not a fan of most conferences. I find that th….
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RT @amruthagujjar: Just got back from @smalldatasf. It’s fascinating how we're seeing this shift from "big" to "small" — not in terms of sc….
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RT @RillData: Develop locally, ship joyfully. This is part of the @smalldatasf manifesto and something we 💯 fully embrace at Rill with our….
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RT @techsontexts: Episode #8:.@jrdntgn on The Analytical Language of John Wilkins by Jorge Luis Borges.
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RT @motherduck: 🎉 We’re officially sold out for Small Data SF next week, though added a few more tickets in case some stragglers want to jo….
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More signs that you might not need a distributed query engine: "The median query scans about 100 MB. The 99.9th percentile query scans about 300 GB.".
My second big finding is the vast majority of queries are tiny, and virtually all queries could fit on a large single node. We maybe don't need MPP systems anymore?
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