Ross ROSS = Recommend OSS · open-source software intelligence for agents

google/googlesql

GoogleSQL(formerly ZetaSQL) - Analyzer Framework for SQL observed · 2026-08-28

github.com/google/googlesql · C++ · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

92/100

  • Activity 98
  • Release rhythm 81
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 69.0
  • age_days: 2696
  • days_rel: 50
  • days_push: 14
  • n_releases_24m: 9

Full methodology

Adoption not part of the score

2638 stars · 258 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

GoogleSQL (formerly ZetaSQL) is a C++ analyzer framework that defines a SQL language—grammar, types, data model, semantics, and function library—and implements parsing and analysis as a reusable component. It is not a database or query engine itself; instead, multiple engines (BigQuery, Spanner, etc.) embed it to get consistent name resolution, type checking, and query analysis, validated via a compliance test suite.

Use cases

  • parse and analyze SQL queries in a custom query engine
  • add consistent SQL language support to my database engine
  • type-check and resolve names in SQL statements
  • validate my engine's SQL implementation against a compliance test suite
  • build tooling to analyze BigQuery SQL queries
  • experiment with the new pipe query syntax
  • get a resolved AST for SQL queries

When to choose

  • you are building a SQL query engine and want consistent language semantics without implementing parsing and analysis yourself
  • you need a production-grade SQL parser and analyzer with a stable resolved AST
  • you want to build tooling that understands queries against BigQuery, Spanner, or other GoogleSQL engines
  • you want to validate your engine's SQL behavior against a reference compliance suite

When to avoid

  • you need a database or query execution engine—GoogleSQL only provides a reference implementation, not a production executor
  • you need a lightweight SQL parser in a language other than C++ or with simple bindings
  • you only need to run queries against an existing database
  • you need full control over SQL dialect semantics that diverge from Google's SQL language

Facets

library · maturity active

parser compiler testing developer-tools databases parsers developer-tools apis cpp cross-platform sql sql-analyzer query-language bigquery spanner type-checking name-resolution compliance-testing pipe-syntax linux macos

1 source

Member repositories

RepositoryRoleHealth v2
google/googlesqlmain92

For agents

markdown · JSON · MCP: product_card(name="google/googlesql")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem