# calogica/dbt-expectations

Port(ish) of Great Expectations to dbt test macros

Repository: https://github.com/calogica/dbt-expectations
Canonical: https://ross.abutalabs.com/products/dbt-expectations
Homepage: https://calogica.github.io/dbt-expectations/
Language: Shell
License: Apache-2.0
License Family: permissive
Topics: dbt
Last push: 2024-12-16T16:31:42+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2141, "days_push": 625, "days_rel": 722, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1234, forks 163 (observed 2026-08-28T04:04:04.702194+00:00)

## What it is
A dbt extension package that ports Great Expectations-style data quality tests as dbt test macros. It lets data teams run expectation tests (column existence, recency, value ranges, schema comparisons) directly in their warehouse via dbt.

## Use cases
- add great expectations style tests to dbt models
- validate data quality in snowflake or bigquery from dbt
- assert table columns and row counts in dbt tests
- check for recent data in warehouse tables
- compare table schemas and aggregations across tables
- run data expectation tests without a separate GE integration

## When to choose
- you already use dbt and want declarative data quality tests in SQL
- you want Great Expectations-like assertions without deploying a separate GE stack
- your warehouse is Postgres, Snowflake, BigQuery, DuckDB, Spark, or Trino

## When to avoid
- you need a standalone data quality framework outside dbt
- you need actively developed features - the package is no longer actively supported
- you use a warehouse or dbt version outside the supported matrix

## Facets
- artifact type: library
- maturity: maintenance
- function: testing, data-science, etl
- domain: databases, analytics, testing
- platform: python, cloud
- tags: dbt, data-quality, great-expectations, sql, data-warehouse, data-tests, data-engineering, postgres

## Member repositories
- calogica/dbt-expectations (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:04.702194+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:22:09.719923+00:00, confidence not recorded.
  - readme: https://github.com/calogica/dbt-expectations (fetched 2026-08-28T04:04:04.702194+00:00, sha 051d8149cff9)
  - homepage: https://calogica.github.io/dbt-expectations/ (fetched 2026-08-29T12:21:32.580918+00:00, sha 74a7ea5eb7bf)
- Data as of 2026-08-30T08:39:29.467469+00:00.