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Apache Hop vs Great Expectations

Apache Hop

hop.apache.org

Great Expectations

greatexpectations.io

Side by side

FigureApache HopGreat Expectations
Price fromFreeFree
Free planYesYes
Free trial——
Open sourceYes—
WebYesYes
WindowsYes—
macOSYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published23
Spec score · Data Preparation for Analytics9.1 (#1)8.1 (#9)
SecurityThe security page advises upgrading to a version containing a vulnerability fix because binary patches are not produced for individual vulnerabilities.GX Cloud metadata is encrypted at rest with AES-256 and in transit with TLS 1.2, and tenant isolation uses Postgres Row Level Security.

Plans

Apache Hop

  • Apache HopFree
  • Apache HopFree

Apache Hop pricing →

Great Expectations

  • DeveloperFree
  • EnterprisePriced on request
  • TeamPriced on request

Great Expectations pricing →

In their own words

Apache Hop

Apache Hop is an open-source platform for data integration and orchestration. Its visual canvas lets users assemble pipelines, preview rows at individual steps, and watch live data and metrics during execution. A pipeline can run locally, on Hop Server, on Apache Spark, or on Flink and Dataflow through Apache Beam. Hop includes more than 250 pipeline transforms, more than 80 workflow actions, and support for over 40 database dialects. Listed connections include PostgreSQL, MySQL, Oracle, SQL Server, Snowflake, BigQuery, Kafka, Salesforce, SAP, S3, REST, and SFTP. Teams can switch environments when moving projects from development to production and keep credentials outside pipeline definitions. Apache Hop is free under the Apache License 2.0. It runs on Linux, macOS, and Windows; Hop Web works in modern browsers. Release 2.19.0 requires Java 21. Docker images and a Kubernetes Helm chart are available; Hop Web is work in progress and provided as-is.

Visit hop.apache.org

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