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Great Expectations (GX Core)

by Great Expectations project (open-source stewardship by Fivetran) · Library · also known as GX, GX Core, great_expectations

Python data-quality framework that declares Expectations about datasets, validates them against pandas, Spark or SQL sources and produces Data Docs

Apache-2.0 licenseOpen sourceFreeLocalSelf-hostedSelf-hostable
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Link verified Nov 2, 2026

Overview

Great Expectations (GX Core) is an open-source Python framework for data quality released under Apache 2.0. Users declare Expectations, such as column values being non-null, unique, within a range, matching a regex or a distribution, group them into Expectation Suites, and run Validations against batches of data from pandas and Spark DataFrames or SQL databases (PostgreSQL, Snowflake, BigQuery, Databricks and others through SQLAlchemy). Checkpoints bundle validations with actions like notifications, and Data Docs render human-readable HTML reports of results. GX integrates with Airflow, Dagster, Prefect and dbt pipelines as a validation step.

The project changed hands in 2026: the GX Cloud hosted product was acquired by FICO and ceased to be publicly available from June 2026, while Fivetran became steward of the open-source GX Core project and community, and the repository now lives under the fivetran GitHub organization (the former URL redirects). The open-source library continues, but teams should expect a transition period and verify the roadmap. GX is heavier to configure than Pandera for simple DataFrame checks, and SQL-oriented alternatives (dbt tests) may suffice for warehouse-only validation.

Editorial note on uncertainty. The greatexpectations.io pricing page still exists but GX Cloud is no longer publicly available per the May 2026 announcement; no pricing_url is recorded and pricing reflects the open-source library only. Governance under Fivetran is recent and may evolve.

Capabilities

  • Declarative Expectations and Expectation Suites
  • Validation against pandas, Spark and SQL data sources
  • Checkpoints with notification actions
  • Data Docs HTML reports
  • Profilers to bootstrap expectations from data
  • Integrations with Airflow, Dagster, Prefect and dbt

Typical workflows

  1. Validate warehouse tables after each pipeline run
  2. Document data contracts with generated Data Docs
  3. Gate model training on input data quality

Strengths

  • Expressive library of built-in expectations
  • Works across DataFrames and SQL sources
  • Apache 2.0

Limitations

  • Configuration-heavy for small projects
  • Hosted GX Cloud discontinued for the public in 2026
  • Stewardship transition to Fivetran is recent

Prerequisites

  • Python environment and access to the data sources being validated

Who it is for

  • Data engineers
  • Analytics teams enforcing data contracts

Alternatives & comparison

  • Dagster

    Asset-oriented Python orchestrator that models pipelines as software-defined data assets with lineage, checks and a hosted Dagster+ option

    Open sourceOpen source
  • dbt

    SQL-first transformation framework that compiles templated models, tests and documentation into warehouse tables; open-source Core plus a commercial platform

    MixedOpen source
  • Pandera

    Lightweight Python library for declaring and validating DataFrame schemas for pandas, Polars, PySpark and other backends, with type-hint style models

    Open sourceOpen source
  • Pydantic

    Python data-validation library using type hints to parse, validate and serialize models, with a Rust core; the schema layer behind FastAPI and many LLM SDKs

    Open sourceOpen source
Compare Great Expectations (GX Core) with its alternatives →

Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

  • License
    great_expectations LICENSE (Apache 2.0)

    https://github.com/fivetran/great_expectations/blob/develop/LICENSE

    Supports: license_spdx, source_model

    github.com/great-expectations/great_expectations redirects to this repository

    checked Nov 1, 2026
  • News
    An update from Great Expectations (2026-05-06)

    https://greatexpectations.io/blog/an-update-from-great-expectations

    Supports: vendor, product_status, pricing_model

    FICO acquired GX Cloud (unavailable publicly from June 1); Fivetran becomes steward of GX Core

    checked Nov 1, 2026
  • News
    Fivetran to become steward of the Great Expectations open source community

    https://www.fivetran.com/press/fivetran-to-become-steward-of-the-great-expectations-open-source-community-and-gx-core-project

    Supports: vendor

    checked Nov 1, 2026
  • Official documentation
    GX documentation

    https://docs.greatexpectations.io/

    Supports: capabilities, integrations

    checked Nov 1, 2026
  • Official site
    Great Expectations

    https://greatexpectations.io/

    Supports: name, summary

    checked Nov 1, 2026
  • Repository
    fivetran/great_expectations

    https://github.com/fivetran/great_expectations

    Supports: repo_url

    checked Nov 1, 2026
Confidence
Medium
Reviewed
Nov 1, 2026
Links
Verified · Nov 2, 2026

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