DataJoint Documentation

Upgrading from 0.14.x?

• Migration guide: Migrate to 2.0
• Legacy docs: datajoint.github.io

About DataJoint

DataJoint implements the Relational Workflow Model—a data model where your database schema defines an executable data pipeline. Tables represent workflow steps, foreign keys encode dependencies, and the system handles job management, parallel execution, and provenance tracking. Object storage integration enables seamless handling of large scientific data.

• Concepts

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  Understand the Relational Workflow Model and DataJoint's core principles

  Learn the concepts

• Tutorials

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  Build your first pipeline with hands-on Jupyter notebooks

  Start learning

• How-To Guides

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  Practical guides for common tasks and patterns

  Find solutions

• Reference

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  Specifications, API documentation, and technical details

  Look it up

• DataJoint Elements

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  Reusable pipeline modules for neurophysiology experiments

  Explore Elements

• DataJoint Platform

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  A cloud platform for automated analysis workflows. It relies on DataJoint Python and DataJoint Elements.

  Learn more | Sign-in

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New to DataJoint? Start with the Quick Start tutorial.