Data Pipelines

Intake

Lightweight tools for loading and sharing data in data science projects.

Status
Generally available
Last checked
Checked · Oct 11, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

Intake is a set of lightweight tools designed to simplify the process of loading and sharing data across various formats and sources, making it easier for data scientists and developers to manage their data pipelines efficiently.

Intake stands out as a lightweight, Python-based tool that simplifies the process of loading and sharing data across various formats and sources without the need for heavy infrastructure.

When it fits — and when it doesn’t

A good fit for

  • Developers who need to load and share data efficiently across multiple formats

  • Data science teams working on projects that require reproducible data pipelines

  • Organizations looking for lightweight, flexible tools for managing data sources

Look elsewhere if

  • Projects requiring real-time data streaming capabilities

  • Teams needing a fully managed cloud service with automatic scaling and monitoring

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 data sources and formats

    Primary support is for Python-based data formats and sources, limited out-of-the-box support for other languages or systems

  2. 02

    Performance issues with large datasets

    Loading large datasets can be slow due to the overhead of Python processing

What it does well

  • Supports multiple data formats and sources

  • Flexible configuration options for data loading

  • Easily extensible with custom plugins

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 Intake

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

Open the setup guide →
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