Last updated Repo data refreshed 24 Oct 20262 options
Our pick · hop
Our pick is Apache Hop for designed, versioned data pipelines: it builds pipelines and workflows visually from metadata and runs them on its own engine or on Apache Beam runners such as Spark and Flink. Apache NiFi is the better fit for continuous dataflows between systems that you watch and adjust while they run, since changes in its UI take effect immediately. Both are licensed Apache-2.0.
★ 1,511 starsLicence: Apache-2.0Last commit 23 Oct 2026Latest release 12 Aug 2026Java
The Hop Orchestration Platform provides a visual and metadata-driven environment for data integration and orchestration, focusing on portability and extensibility.
Best for: Users seeking a highly portable, visually-driven, and metadata-centric platform for orchestrating diverse data pipelines and workflows.
What's good
Employs a metadata-driven approach that enhances reusability and simplifies the maintenance of data pipelines.
Supports highly portable data pipelines that can be executed across diverse environments and cloud platforms.
Features a visual designer for creating complex transformations and workflows without extensive coding.
Designed for robust orchestration of various data integration tasks and workflows.
Watch out for
Offers fewer pre-built connectors compared to more specialized ELT tools, potentially requiring custom development.
The visual design paradigm might be less flexible for developers accustomed to code-first tools.
Community support, while active, is smaller than some of the largest Apache projects.
Apache NiFi is a robust system designed for automating data flow between systems, offering a web-based user interface for creating, monitoring, and managing data pipelines.
Best for: Enterprises needing highly reliable, complex, and real-time data flow automation with granular control and strong security.
What's good
Provides a powerful visual interface for designing and managing complex, real-time data flows.
Offers guaranteed delivery, robust error handling, and data provenance tracking capabilities.
Features an extensible architecture that supports custom processors and integration points.
Includes strong security features for data access and flow management.
Watch out for
Can be complex to set up and configure, particularly for advanced or high-volume deployments.
Requires significant system resources (memory and CPU) for demanding data processing tasks.
The extensive feature set and unique dataflow paradigm contribute to a steeper learning curve.
"Dormant" means no commit pushed to the default branch in the last 12 months. "Archived" means the maintainers have marked the repository read-only on GitHub. "Deprecated" means the project's README says it is deprecated or no longer maintained. Stars, licence, commit and release dates come from the GitHub API (GitLab for projects developed there) and are cached for up to 24 hours. The written analysis is AI-assisted and checked against that data.
Designed pipelines vs live dataflows
Apache Hop is a metadata-driven data integration and orchestration platform: pipelines and workflows are designed visually, then managed like any other software project. Depending on the engine and transforms used, Hop processes data in batch, streaming or a mix of the two, on its own engine or on Apache Beam runners such as Spark and Flink.
Apache NiFi was built to automate the flow of data between systems. Its design follows flow-based programming, and changes made to a running dataflow in its UI take effect immediately.
Apache Hop originated from the same code base as Kettle, better known as Pentaho Data Integration, and is now an independent Apache project. Teams comparing NiFi with Pentaho are usually choosing between NiFi's live dataflows and Kettle-style designed pipelines, which is the choice this page covers. Hop's documentation also explains how to import existing Kettle projects.
Pick Hop for scheduled data integration work, such as populating and maintaining a data warehouse, where pipelines are designed, tested and versioned. Pick NiFi for always-on flows between systems that operators need to watch and change while they run.
Apache Hop originated from the same code base as Kettle (Pentaho Data Integration). It is now an independent Apache project with its own concepts, configuration and engines.
Yes. Hop's documentation lists processing streaming data, for example from Apache Kafka, on its own or alongside batch; whether a pipeline runs as batch or streaming depends on the engine and transforms used.
Apache Hop and NiFi are active: each has had a commit in the last 12 months (most recent: Apache Hop on 23 Oct 2026, NiFi on 23 Oct 2026). Status is checked against GitHub daily.
What licences do Apache Hop and NiFi use?
Apache Hop: Apache-2.0; NiFi: Apache-2.0. Check each project's licence file before use.
