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Head-to-head · DataOps Platforms

Apache Hop vs Prefect

  • Updated Oct 2026
  • Both researched from official sources
  • 1 check side by side
Higher score Apache Hop #3 in DataOps Platforms 9.0/10 Free plan Free plan✓ 0 of 4 features Visit Apache Hop
Prefect #7 in DataOps Platforms 8.6/10 Free plan Free plan✓ 0 of 4 features Visit Prefect

Apache Hop leads on 0 checks, Prefect on 0, and 1 is even. Who comes out ahead on the 1 yes/no, price and count check where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreApache Hop · 9.0/10
  • Free planboth

Apache Hop scores higher on our rubric for dataops platforms: 9.0 against 8.6 out of 10; our editors rank them #3 and #7.

Apache Hop is the better fit for teams building visual ETL and data pipelines. Prefect is the better fit for python teams needing observable hybrid orchestration.

  • Apache Hop fits best

    Teams building visual ETL and data pipelines

  • Prefect fits best

    Python teams needing observable hybrid orchestration

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Side by side

Feature Apache Hop 9.0/10 Visit ↗ Prefect 8.6/10 Visit ↗
At a glance
Editor score 9.0 8.6
Ranking #3 in DataOps Platforms #7 in DataOps Platforms
Best for Teams building visual ETL and data pipelines Python teams needing observable hybrid orchestration
Pricing model Free Free plan + paid
Starting price Free plan $100/mo
Free plan ✓ ✓
Free trial — —
Deployment Cloud, Self-hosted, Desktop Cloud, Self-hosted
Platforms Windows, macOS, Linux Web
Support Community, Docs Community, Docs
Built for Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Features Apache Hop 0/4 · Prefect 0/4
Workflow scheduling Not checked yet Not checked yet
Pipeline monitoring Not checked yet Not checked yet
Data quality checks Not checked yet Not checked yet
Version control Not checked yet Not checked yet
Specs
Deployment options Not checked yet Not checked yet
Supported integrations Not checked yet Not checked yet
Our review
Pros
  • 250+ transforms, 80+ workflow actions, and metadata-driven design
  • Runs locally, on servers, containers, Spark, Flink, and Dataflow
  • Supports CDC plus 40+ database dialects and named warehouse connectors
  • Track flow-run states, logs, schedules, and events in one platform.
  • Configure retries and delays, event automations, and webhook triggers.
  • Run workflows in Prefect Cloud, customer infrastructure, or hybrid setups.
Cons
  • Deployment spans several runtimes, adding architecture decisions
  • Scripting transforms require JavaScript, Java, Groovy, or Python skills
  • Support channels are centered on community resources and documentation
  • Workflow definitions are Python-based, not built with a visual workflow editor.
  • Hobby lacks the webhooks and bring-your-own-compute highlights of Starter.
  • Team pricing is $100 per user per month, rather than a flat monthly fee.
Our verdict

Apache Hop is an open-source data orchestration, engineering, integration, and ETL platform from the Apache Software Foundation. Its visual environment is designed for data engineers and teams that need repeatable pipelines and workflows…

Read the review →

Prefect is a Python-based orchestration platform for data, machine-learning, durable-execution, and agent workflows. Teams define flows and tasks in Python, then deploy to Prefect Cloud, their own infrastructure, or hybrid environments.…

Read the review →
  1. Apache HopDataOps Platforms 9.0Free plan
  2. PrefectDataOps Platforms 8.6Free plan

Strengths and trade-offs

  • Apache Hop — where it wins

    • 250+ transforms, 80+ workflow actions, and metadata-driven design
    • Runs locally, on servers, containers, Spark, Flink, and Dataflow
    • Supports CDC plus 40+ database dialects and named warehouse connectors

    Where it doesn't

    • Deployment spans several runtimes, adding architecture decisions
    • Scripting transforms require JavaScript, Java, Groovy, or Python skills
    • Support channels are centered on community resources and documentation

  • Prefect — where it wins

    • Track flow-run states, logs, schedules, and events in one platform.
    • Configure retries and delays, event automations, and webhook triggers.
    • Run workflows in Prefect Cloud, customer infrastructure, or hybrid setups.

    Where it doesn't

    • Workflow definitions are Python-based, not built with a visual workflow editor.
    • Hobby lacks the webhooks and bring-your-own-compute highlights of Starter.
    • Team pricing is $100 per user per month, rather than a flat monthly fee.

More comparisons

All DataOps platforms comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update