Strata - Expressive semantic layer that can say no to your LLM
Show HN: Strata – an expressive semantic layer that can say no to your LLM
Strata is a semantic layer that brings discipline to AI-powered analytics. It runs in Docker with a bundled database, letting you model data from Snowflake, Databricks, PostgreSQL, and more using YAML. Your coding agent reads AGENTS.md to propose fact and dimension tables, fields, and joins, then waits for your approval. Strata enforces naming rules and join constraints, so it can refuse invalid queries instead of hallucinating. Deploy to your own server and explore blended reports. Try it free on your machine.
Drag a measure from one fact next to a dimension from another and watch it blend, or refuse with a reason.
- chrisweekly
> "Not a fit? That is fair.
If all you want is another query tool for SQL-fluent analysts, Strata is not it. We are built to take powerful self-service to everyone else, the people who could never write the query in the first place."
Every product should include this kind of disclaimer. Clarity on what it's NOT is often more immediately illuminating than (usually more verbose) descriptions of what it IS.
Anyway, this looks like it could be useful - though I'd find it much more compelling if it were OSS.
- irasigman
How do you weight the value of semantic layers when all of the labs are chasing shell usage benchmarks like TerminalBench?
Aside from the enterprise stuff like consistent metrics I’m not convinced semantic layers improve agent performance. Case in point is Snowflake Analyst has been routing 90%+ of queries to traditional SQL as opposed to their own semantic SQL dialect.
A semantic layer is a concept from 2018 in the BI world. Metadata is one thing but semantic layer implies an abstraction from physical data with lossy translations.
- efromvt
I’m a big fan of the strict naming as an abstraction above tables and reuse as blend key approach, it also greatly simplifies aggregate resolution like you have. (Landed on the same abstraction level when building a semantic model personally).
Lots of 404s on the docs pages - might be worth an audit of links?