Data Pipelines

dstack

Automate data and training workflows with dstack.

Status
Generally available
Last checked
Checked · Oct 16, 2026
License
Open source
Pricing
Free tier · from $0
Visit dstack Compare with alternatives

What it is

dstack is an open-core tool designed to automate data and machine learning workflows. It simplifies the process of managing experiments, tracking metrics, and deploying models efficiently.

dstack stands out as an open-source tool specifically designed to automate data and training workflows, offering comprehensive tracking and deployment capabilities.

When it fits — and when it doesn’t

A good fit for

  • Teams needing to automate and track complex data science workflows

  • Projects requiring efficient model deployment and tracking metrics

Look elsewhere if

  • Users looking for a fully managed cloud service without self-hosting capabilities

  • Small projects that do not require extensive workflow automation or tracking features

Known weaknesses

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

  1. 01

    Limited language support beyond Python

    Primary development focuses on Python, secondary languages like TypeScript have community-maintained SDKs with limited features

  2. 02

    Small and less active community

    GitHub repository shows low activity levels compared to more established ML platforms

What it does well

  • Automates data and training workflows

  • Tracks experiment metrics

  • Simplifies model deployment

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 dstack

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

Open the setup guide →
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