GX (Great Expectations)

 GX, formerly Great Expectations, is an open-source data quality framework created by Abe Gong and James Campbell. Teams declare Expectations, verifiable assertions such as column ranges, null thresholds, and schema rules, then validate dataframes and warehouse tables against them inside pipelines. GX Cloud adds a managed interface where analysts create and monitor validations without writing code. Validation results render as readable data docs, which turn quality checks into documentation stakeholders can review without code access.

Key Capabilities:

• Library of prebuilt Expectations for common data quality rules

• Validation across Pandas, Spark, Snowflake, Databricks, and SQL sources

• Checkpoints that gate pipeline runs on validation results

• Automatic data documentation from validation outcomes

• Airflow and Dagster integrations for in-pipeline checks

• Apache 2.0 core with the managed GX Cloud service

See GX (Great Expectations) pricing details →