Data Pipelines

MLRun

Build, run, and monitor ML tasks and pipelines efficiently.

Status
Generally available
Last checked
Checked · Oct 16, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

MLRun is a generic mechanism for data scientists to build, run, and monitor machine learning tasks and pipelines. It simplifies the process of managing complex workflows and automates many aspects of model deployment and monitoring.

MLRun stands out by offering a comprehensive, self-hosted solution for managing ML tasks and pipelines, with strong support for automation and monitoring.

When it fits — and when it doesn’t

A good fit for

  • Data science teams looking to streamline their model deployment and monitoring processes

  • Organizations that require self-hosted infrastructure for compliance or security reasons

  • Developers who need a flexible tool to integrate with existing data processing pipelines

Look elsewhere if

  • Teams requiring cloud-based managed services without the need for self-hosting

  • Projects where real-time model deployment and monitoring are critical

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited integrations with non-Python frameworks

    Primary support is for Python-based ML libraries and tools like Dask, Spark, and Nuclio

  2. 02

    Performance issues in large-scale deployments

    Scalability tests show performance degradation with more than 10 concurrent pipelines

What it does well

  • Automated model deployment and monitoring

  • Support for various ML tasks and pipelines

  • Integration with popular data processing frameworks

  • Self-hosted infrastructure management

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up MLRun

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
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MLRun — tracked on AI Navigator

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