Data tooling,
indexed.
A reference catalog of tools in the modern data stack — structured for comparison, sourced from vendor documentation, free of paid placement, verified by hand. Three views of the same data: by cluster, by capability, by tool.
Three clusters, one vertical.
Quality
& testing
11 tools indexed
Pre-production and post-production checks on warehouse correctness, freshness, and schema. Where your data quality story actually starts.
Browse cluster →Catalog
& discovery
7 tools indexed
Asset inventory, business glossary, ownership tracking, and search for warehouse data.
Browse cluster →Lineage
& metadata
3 tools indexed
Cross-system data flow tracking, impact analysis, and column-level lineage from source through consumption.
Browse cluster →The full ledger.
Cut the index by feature.
One schema, three cuts.
Each tool is placed in a primary cluster — the problem it was built for — and scored 0–3 against every cluster in the vertical. A tool with a primary cluster of quality testing and a strength of 2 against lineage appears on the quality hub as a primary entry and on the lineage hub as a strong secondary entry.
Categories, scoring rubrics, sourcing, and verification cadence are documented in full on the methodology page.
What this catalog is.
Data Stack Index is a structured reference for data tooling. Every tool is described against the same schema — deployment, pricing, capabilities, integrations, alternatives — so that two tools can be compared on the same fields rather than on incompatible vendor language.
The catalog is free, takes no money from vendors, and lists no tool because the vendor asked. Selection criteria, categorization, sourcing, and update cadence are documented on the methodology and independence pages. The project is built and maintained by one person; the coverage page is honest about what's indexed and what isn't.