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Michael Stonebraker finds Text-to-SQL accuracy at 10% on real enterprise data

Michael Stonebraker, a Turing Award winner, evaluated text-to-SQL capabilities on a real enterprise data warehouse. His findings revealed a low accuracy rate of only 10%, significantly underperforming against an 80% benchmark. This result reinforces Stonebraker's past critiques of database technologies and suggests current text-to-SQL systems struggle with real-world enterprise data complexity. AI

IMPACT Highlights significant limitations in current text-to-SQL accuracy for enterprise applications, suggesting a need for further research and development.

RANK_REASON Academic research/evaluation of a specific AI capability (text-to-SQL) on real-world data.

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Michael Stonebraker finds Text-to-SQL accuracy at 10% on real enterprise data

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0 / 100
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Research
Academic research/evaluation of a specific AI capability (text-to-SQL) on real-world data.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, other
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High
Clearly on-topic for AI-industry coverage.
Story freshness
151 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · DataRecce ·

    Michael Stonebraker was right about CODASYL. Right about NoSQL. Now he's run text-to-SQL on a real enterprise warehouse and got 10% accuracy against an 80% benc

    Michael Stonebraker was right about CODASYL. Right about NoSQL. Now he's run text-to-SQL on a real enterprise warehouse and got 10% accuracy against an 80% benchmark. The pattern is hard to ignore. https:// blog.reccehq.com/benchmarks-li e-what-a-turing-award-winner-found-when-he…