Databases should contain their own Metadata – Use SQL Everywhere

Floe promises “self-aware” databases — commenters scream déjà vu

TLDR: Floe claims a database that exposes rich “data about your data” as simple SQL tables, promising answers about speed, cost, and usage without extra dashboards. Commenters are split between “we’ve had this forever” and “this goes further with lineage and costs,” with a side of meme-fueled snark.

A startup called Floe says your database should tell you about itself — who’s using it, what’s slow, what’s huge — all answerable with plain old SQL. Their pitch: put all the “data about your data” (metadata) inside the database as queryable system tables, so you don’t need extra dashboards or logs. They even crack a pun about “table stakes,” and tease a beta, GitHub in tow.

The crowd? Immediately split. One camp rolled its eyes: veterans asked if this is just the same “information schema” every major database already has. Another camp pushed back, saying Floe isn’t just listing tables — it’s making everything queryable: stats, lineage (where data came from), freshness, access patterns, even cost and latency. Translation: not just “what tables exist,” but “who touched what, when, and how much it cost” — all with SQL. Meanwhile, a drive‑by heckler yelled “AI slop,” because it’s the internet.

The drama hits that familiar nerve: innovation or marketing? Fans want fewer dashboards, more answers in one place. Skeptics smell a rebrand of features databases have had for years. Bonus meme: the post’s quip about “suffering Grafana together” turned into a running joke, with commenters picturing a world where your database admits, “It’s me. Hi. I’m the problem, it’s me.”

Key Points

  • Floe embeds a comprehensive, queryable metadata model inside the database, exposed via a dedicated `sys` schema.
  • System views include `sys.table`, `sys.view`, and `sys.table_column`, with columns linked to types (`sys.type`) and statistics generated by Floecat.
  • Example SQL queries demonstrate how to estimate table sizes and locate tables with columns meeting certain criteria (e.g., a “country” column with >2 values).
  • The approach is positioned as an alternative to external dashboards, verbose logs, or core dump collection for diagnostics.
  • Floe’s Lakehouse SQL compute engine is under active development and targeting a beta release soon.

Hottest takes

"Isn't this like it is in many relational databases" — galaxyLogic
"the key difference is making that metadata first-class and queryable across the whole system" — umairnadeem123
"AI shit slop" — ewuhic
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