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SPECIFICTION
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Atlas vs Great Expectations

Atlas

atlasgo.io

Great Expectations

greatexpectations.io

Side by side

FigureAtlasGreat Expectations
Price from$9/moFree
Free planYesYes
Free trialYes—
Open sourceYes—
WebYesYes
WindowsYes—
macOSYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published83
Spec score · Database Testing Tools9.5 (#1)8.2 (#9)
FoundedLinkedIn lists the company as founded in 2021.2018

Plans

Atlas

  • Atlas StarterFree
  • Atlas StarterFree
  • Atlas Pro (Team)$9 a month
  • Atlas Pro (Team)$9 a month
  • Atlas Schema Monitoring$39 a month
  • Atlas Schema Monitoring Pro$39 a month
  • Atlas Pipelines Pro$59 a month
  • Atlas EnterprisePriced on request

Atlas pricing →

Great Expectations

  • DeveloperFree
  • EnterprisePriced on request
  • TeamPriced on request

Great Expectations pricing →

In their own words

Atlas

Atlas is a language-independent tool for managing database schemas and migrations through declarative, versioned workflows. It compares a database's current state with a desired schema expressed in HCL, SQL, or an ORM format, then can generate and execute a migration plan. Teams can lint and validate migrations, run safety checks, and test schemas and migrations. The open version supports PostgreSQL, MySQL, MariaDB, SQLite, TiDB, and LibSQL; Pro adds drivers including SQL Server, Oracle, Snowflake, and Databricks. Atlas describes its core engine as open source under Apache 2.0, with advanced features in proprietary versions. Integrations include Kubernetes, Terraform, GitHub Actions, GitLab CI, CircleCI, Bitbucket Pipelines, Azure DevOps, and a Go SDK. Starter is free. Atlas Pro costs $9 per developer per month, plus usage-based pricing for CI/CD pipelines and databases; new users can try Pro for 30 days. Schema Monitoring costs $39 per monitored database per month. Enterprise pricing is custom.

Visit atlasgo.io

Great Expectations

Great Expectations (GX) is a framework for defining data tests and checking whether data meets their criteria. GX Core is a Python library for building and running data-validation workflows, and it requires Python versions 3.10 through 3.13. GX Cloud provides a web interface for data teams, including technical and nontechnical stakeholders, and runs tests in the environment where connected data resides using read-only connections. Data Docs turns Expectations, validation results, and related metadata into static web pages. GX lists data-source integrations including Databricks, BigQuery, Pandas, PostgreSQL, Snowflake, Spark, Redshift, and cloud storage services. Notification integrations include Slack, Email, PagerDuty, OpsGenie, and Microsoft Teams; orchestration integrations include Apache Airflow, Dagster, and Prefect. Custom rules can be written with SQL in GX Cloud or through GX Core. The Developer plan costs nothing and covers up to five data assets under test per month and three users, with unlimited rows per asset. Team and Enterprise have custom data-asset limits and no listed prices.

Visit greatexpectations.io