Apache Hop vs DataKitchen TestGen
Apache Hop
hop.apache.org
DataKitchen TestGen
datakitchen.ioSide by side
| Figure | Apache Hop | DataKitchen TestGen |
|---|---|---|
| Price from | Free | $100/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 2 |
| Spec score · DataOps Platforms | 9.0 (#2) | 9.2 (#1) |
| Deployment | The download page provides Docker images for Hop and Hop Web and a Helm chart for Kubernetes; Hop Web is described as work in progress and provided as-is. | TestGen is self-hosted inside the customer network using Docker Compose by default or Helm on Kubernetes for production. |
| Licence | Apache Hop is released under the Apache License 2.0. | The core engine and open-source edition are licensed under Apache 2.0; Enterprise uses a DataKitchen subscription licence. |
| Purpose | Apache Hop is an open source platform for data integration and orchestration, with visual pipelines and workflows. | TestGen profiles databases and automatically generates data quality tests, with dashboards for results and quality scores. |
| Release news | Apache Hop 2.19 was announced in August 2026 with Marketplace changes, native Spark updates, Databricks filesystem support, SFTP metadata and UI improvements. | The 14 October 2026 open-source 5.134.0 release added DuckDB and file sources, migration comparison, new tests, resumable profiling and expanded notifications. |
| Security | The security page advises upgrading to a version containing a vulnerability fix because binary patches are not produced for individual vulnerabilities. | The security documentation describes HTTPS support, AES-256-CBC encryption for database credentials at rest, and enterprise SSO through OpenID Connect. |
| Support | Community support is volunteer-based and free, but the project says it cannot promise response times; commercial providers offer services such as SLAs, training, and migration. | The open-source plan includes community support, and Enterprise includes direct DataKitchen support and priority access to releases. |
| System requirements | The installation guide lists Windows 7 or later, Linux x86_64 or ARM, macOS and modern browsers for Hop Web. | Mac and Linux installation requires Python 3.9 or newer; Docker mode requires Docker 27 or newer and Compose 5.0 or newer. |
| What it does | Apache Hop is a metadata-driven platform for visual data integration, engineering and orchestration using pipelines and workflows. | TestGen profiles databases, generates data-quality tests, executes them, monitors tables and produces quality scores. |
Plans
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.
DataKitchen TestGen
DataKitchen TestGen profiles databases, generates data quality tests, and shows results and quality scores in dashboards. Its listed checks include 55 profiling characteristics, 32 hygiene detector tests, and 49 test types, including generated tests, business rules, and custom SQL. Monitors cover freshness, volume, schema, and custom metrics, using predictive models to flag changes such as late arrivals and schema drift. Supported databases include Snowflake, Databricks SQL, Azure Synapse Analytics, Azure SQL Database, SQL Server, OneLake, BigQuery, Redshift, Aurora PostgreSQL, Oracle 12c and later, SAP HANA, PostgreSQL, and Salesforce Data 360. It can also profile and test structured data in Iceberg, Parquet, Avro, ORC, CSV, and JSON through supported external-table options. TestGen runs in the customer’s infrastructure; DataKitchen says it does not host the application or receive customer data. It queries target databases with read-only access and stores results and metadata in its application database. The free Open Source plan is limited to one user, one connection, and one project. Enterprise costs $100 a month, billed per user and per database connection.