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tbrannan

HN member
Joined
Fri, Apr 05, 2024, 2:36 AM UTC
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17 items

About tbrannan

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Recent public activity

  1. comment
    Comment #46529033

    Great minds think alike!

  2. comment
    Comment #46528998

    because it is, but its still true lol

  3. comment
    Comment #46521190

    Thanks!! means a lot coming from you. Best of luck at Supabase.

  4. comment
    Comment #46516543

    Really appreciate the input. I'll make sure to give you early access once we implement this, I'll keep you posted.

  5. comment
    Comment #46516339

    Noted, we've been focused on Postgres first but SQL Server keeps coming up. Appreciate the feedback.

  6. comment
    Comment #46515276

    I haven’t come across anything else like this. It’s genuinely impressive.

  7. comment
    Comment #46514602

    This is useful. What if you ran a CLI locally that extracts just the statistical profile from prod cardinality, relationship ratios, etc. and uploaded that? We'd never touch your d…

  8. comment
    Comment #46513882

    Not yet, but you're the second person in this thread to call out distribution control as a gap. It's on our radar now. Thanks for the feedback.

  9. comment
    Comment #46513273

    That is a really good point one-to-many relationships blow up fast. The trunk table idea is interesting, would simplify how people reason about limits. Appreciate the feedback, gen…

  10. comment
    Comment #46513249

    Appreciate the Snaplet comparison, they were doing good work. You're right that realistic looking strings are the easy part. We're focused on relational integrity first (FKs, const…

  11. comment
    Comment #46513145

    Different focus, ShadowTraffic is config-driven and optimized for streaming/Kafka workloads. We're schema-driven: point us at your DDL and we generate relational test data automati…

  12. comment
    Comment #46513081

    Thanks for the feedback! Honestly, we're still dialing in the tiers, what row limits would feel reasonable to you for your use case? Always helpful to hear what people actually nee…

  13. comment
    Comment #46512572

    Thanks! At 1M rows, I think a few things matter: Streaming: Can't hold it all in memory. Generate in chunks, write, release, repeat. Format choice: Parquet with row groups is fast …

  14. comment
    Comment #46512308

    Thanks! To clarify, the core engine isn't AI. It's deterministic pattern matching, so it runs in milliseconds with no token costs. There's an optional "Story Mode" that uses AI for…

  15. story
  16. story
    Show HN: DDL to Data – Generate realistic test data from SQL schemas

    I built DDL to Data after repeatedly pushing back on "just use production data and mask it" requests. Teams needed populated databases for testing, but pulling prod meant security …

  17. comment
    Comment #46505160

    I recently learned about the hooks and skills feature. This is cool