Soda
Data quality testing defined in a readable check language
Soda is profiled here as a Data Quality tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Soda is a data quality platform built around Soda Core, an open-source CLI, and the SodaCL check language. Engineers write checks for freshness, completeness, schema, and custom SQL conditions in YAML, then run them against warehouses and pipelines to catch bad data before it spreads downstream. Soda Cloud adds monitoring, anomaly detection, and collaboration on top of the open-source scanner. Writing checks in a readable language lets data and engineering teams collaborate on quality rules without deep tooling knowledge. The scanner plugs into orchestrators and transformation tools, so checks run as part of existing pipelines.
Key Capabilities:
SodaCL language for declaring data quality checks
Validation across Snowflake, BigQuery, Databricks, Postgres, and Spark
Checks for freshness, completeness, validity, and schema
Anomaly detection on metrics over time in Soda Cloud
Pipeline integration with Airflow, dbt, and CI tools
Apache 2.0 Soda Core with a managed cloud option
Alternative tools
- Datafold
Data diffing and regression testing for data teams
- Anomalo
Automated data quality monitoring with machine learning
- Elementary
dbt-native data observability and anomaly detection
- GX (Great Expectations)
Declarative data quality testing for pipelines