# sodadata/soda-core

Data Contracts engine for the modern data stack. https://www.soda.io

Repository: https://github.com/sodadata/soda-core
Canonical: https://ross.abutalabs.com/products/soda-core
Homepage: https://go.soda.io/core-docs
Language: Python
License: NOASSERTION
License Family: other
Topics: python, data-engineering, data-governance, data-monitoring, data-observability, data-profiling, data-quality, data-quality-checks, data-quality-monitoring, data-reliability, data-testing, data-unit-tests, data-validation, dataquality, datatesting, dbt, pipeline-testing, snowflake, data-quality-testing, data-contracts
Last push: 2026-08-26T08:28:03+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 99, longevity 100
- inputs: {"age_days": 2088, "days_push": 7, "days_rel": 8, "gap_med": 7, "n_releases_24m": 52}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2417, forks 283 (observed 2026-08-28T04:06:50.413198+00:00)

## What it is
Soda Core is a data quality and data contract verification engine that lets teams define data quality contracts in YAML and validate schema and data across their data stack. It ships as a Python library and CLI supporting many data sources like PostgreSQL, Snowflake, BigQuery, and Databricks, with 50+ built-in checks.

## Use cases
- validate data quality in pipelines before they run
- define data contracts in yaml for tables
- run data quality checks on snowflake and bigquery
- detect schema drift and anomalies in data warehouses
- embed data tests in airflow or dagster pipelines
- profile and monitor datasets for reliability issues

## When to choose
- you need declarative, YAML-based data quality checks across multiple warehouses
- you want to enforce data contracts as part of your ELT pipelines
- you need a CLI and Python API for data validation with broad data source support

## When to avoid
- you need a full data observability platform with anomaly detection without Soda Cloud
- your checks are only simple unit tests on Python code rather than data
- you require a GUI-first data quality tool

## Facets
- artifact type: cli-tool
- maturity: active
- function: testing, monitoring, etl, cli, developer-tools
- domain: analytics, databases
- platform: python, cli, cross-platform
- tags: data-contracts, data-quality, data-observability, yaml-configuration, dbt, snowflake, bigquery, data-pipelines, data-engineering, devops

## Member repositories
- sodadata/soda-core (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:50.413198+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 2026-08-30T02:33:08.255698+00:00, confidence not recorded.
  - readme: https://github.com/sodadata/soda-core (fetched 2026-08-28T04:06:50.413198+00:00, sha c0f1f8dedeb9)
- Data as of 2026-08-30T08:39:29.467469+00:00.