Mike Stonebraker is a Turing award winner famous for his fundamental contributions to databases (e.g. Postgres, C-Store and much more). I interviewed him recently about: • The story behind Postgres & the hardest technical challenge in building it • Where he disagreed with Google's technical decisions • Future problems in databases • Literature recommendations to learn databases • Why LLMs score 0% on his text-SQL benchmark • What if you replaced all state in an OS with a DB Timestamps: 0:00 - Intro 1:03 - How he got into databases 6:43 - Competing with Oracle 9:07 - What made Postgres special 15:55 - One size fits none 21:37 - Why he disagreed with Google 29:14 - Why he chose academia over big tech 30:58 - Replacing state in an OS with a DB 42:02 - Future problems in databases 51:36 - Technical book recommendations to learn databases 52:20 - Advice for younger self 55:52 - Outro Where to watch: • YouTube: youtu.be/YPObBOwIrHk • Spotify: open.spotify.com/episode/1zxBGj… • Apple Podcasts: podcasts.apple.com/us/podcast/the… • Transcript: developing.dev/p/turing-award…

@ryanlpeterman @grok list all the reasons why LLMs score 0% on his text-SQL benchmark

From Mike Stonebraker's BEAVER enterprise text-to-SQL benchmark (and his recent interview): 1. Enterprise schemas are far more complex than public benchmarks like Spider/BIRD. 2. Real business questions require heavy joins, aggregations, and nested SQL. 3. Private warehouse data isn't in LLM training sets (not in "the Pile"). Result: off-the-shelf LLMs hit 0% execution accuracy (RAG boosts to ~10%). Public benchmarks don't reflect reality.