Amazon Deequ
6.7#2 in data quality testing toolsFree planFree planAPILinuxmacOSSelf-hosted
VisitAmazon Deequ vs Datafold
What both publish
| Fact | Amazon Deequ | Datafold |
|---|---|---|
| Integrations | Deequ is built on Apache Spark, is distributed through Maven artifacts, and has a Python interface called PyDeequ. | The product page names Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, GitHub, and GitLab, and says Datafold integrates with 50+ data tools. |
| Purpose | Deequ is an Apache Spark library for defining unit tests that measure data quality in large datasets. | Datafold combines specialized AI agents, a context layer, and data quality tools to automate data engineering. |
Amazon Deequ plans
- Apache 2.0 open-source libraryFree
Datafold plans
- Custom pricingPriced on request
Pick Amazon Deequ if…
Deequ suits developers and data teams who want to check data quality in Spark-based pipelines before datasets reach consuming systems or machine-learning algorithms. It is intended for users comfortable working with Spark and its supported release versions.
Pick Datafold if…
Datafold suits teams that need schema migration tests and data quality checks across its supported databases. It is a fit for users comfortable writing tests in SQL or YAML.