[opensourcedex]

Airbyte is a free, open source data engineering & integration project written in Python and released under a custom open-source licence. It has 22,082 GitHub stars, 5,350 forks and 2,395 open issues, and was last pushed 5 hours ago. On this registry it ranks #1 of 39 tracked projects in Data Engineering & Integration, with 5 head-to-head comparisons available. It gained 36 stars over the last 6 tracked days.

Airbyte — Open-source data integration for modern teams

What is Airbyte?

What it is

Airbyte open-source data movement project. It lives in data engineering and data integration ecosystem. It moves data from APIs, databases, and files into warehouses, data lakes, and AI applications. It supports ELT and ETL pipelines. It also supports AI agents needing business data.

Concrete problem: teams need centralize long tail of data sources. Custom connector development needs support. Data engineers need customize existing connectors. AI teams need real-time context from CRMs, support tools, SaaS APIs, and databases. Airbyte addresses this with connector catalog, self-hosted and Cloud deployment, no-code and low-code connector tools, orchestration integrations, and Agent SDK. It provides registry report listing connectors available in Airbyte or Airbyte Cloud. Demo app lets users test platform.

Key capabilities

  • Catalog lists 600+ connectors for APIs, databases, data warehouses, data lakes, and AI applications.
  • Airbyte moves data into warehouses, lakes, or databases for ELT and ETL pipelines.
  • Connector Builder and low-code CDK create connectors with no-code UI or configuration.
  • Orchestration works with Airflow, Dagster, Kestra, and Airbyte API.
  • Agent SDK installs with uv pip install airbyte-agent-sdk and embeds type-safe connectors as LLM tools.
  • Agent SDK works with pydantic-ai, LangChain, OpenAI Agents, and FastMCP, with retry, exception translation, and output-size guardrails.
  • Airbyte Agents provides managed data and context layer for AI agents.

Who uses it and how

  • Data teams centralize sources into warehouses, lakes, or databases with Airbyte Open Source or Airbyte Cloud.
  • Data engineers create or customize connectors using Connector Builder or low-code CDK.
  • Platform teams orchestrate syncs through Airflow, Dagster, Kestra, or Airbyte API.
  • AI application teams give agents, LLMs, and MCP clients real-time access to CRMs, support tools, SaaS APIs, and databases.
  • Community users follow public roadmap, Slack, and GitHub discussions for connector and platform work.

Getting started

Deploy Airbyte Open Source from quickstart or set up Airbyte Cloud. Install Agent SDK with uv pip install airbyte-agent-sdk.

When to use it — and when not to

Use when open-source data movement and AI-agent data access matter, and Cloud or self-hosted deployment fits. Avoid when license NOASSERTION blocks policy review, or when 2395 open issues and 0 contributors count suggest support risk. Facts list no paid replacement comparison and no required database, storage, or SMTP details, so self-hosting needs extra operational discovery.

project readme (upstream, from github) — read inline

Airbyte

Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications

Test Release Slack YouTube Channel Views Build License License

We believe that only an open-source solution to data movement can cover the long tail of data sources while empowering data engineers to customize existing connectors. Our ultimate vision is to help you move data from any source to any destination — whether that destination is a data warehouse, a data lake, or an AI agent. Airbyte provides a catalog of 600+ connectors for APIs, databases, data warehouses, data lakes, and AI applications.

Airbyte Connections UI Screenshot taken from Airbyte Cloud.

Pick the right Airbyte Platform for the job

  • Moving data into warehouses, lakes, or databases (ELT / ETL) → use Airbyte Open Source (this repo) or Airbyte Cloud. 600+ connectors for APIs, databases, data warehouses, and data lakes.
  • Giving AI agents, LLMs, or MCP clients real-time access to business data (CRMs, support tools, SaaS APIs, databases) → use Airbyte Agents, the managed data and context layer for AI agents, or the open-source Agent SDK (uv pip install airbyte-agent-sdk) to embed type-safe connectors as LLM tools. Works with pydantic-ai, LangChain, OpenAI Agents, and FastMCP, with built-in retry, exception translation, and output-size guardrails.

Getting Started — Data Movement (ELT)

For moving data into warehouses, lakes, and databases:

Try it out yourself with our demo app, visit our full documentation, and learn more about recent announcements. See our registry for a full list of connectors already available in Airbyte or Airbyte Cloud.

Getting Started — AI Agents

For building AI agents that need real-time business data:

  • Read the Airbyte Agents documentation to use the managed product.
  • Or install the open-source Agent SDK: uv pip install airbyte-agent-sdk. Works with pydantic-ai, LangChain, OpenAI Agents, and FastMCP — see the SDK README for examples of turning a connector call into an LLM tool.

Join the Airbyte Community

The Airbyte community can be found in the Airbyte Community Slack, where you can ask questions and voice ideas. You can also ask for help in our Airbyte Forum. Airbyte's roadmap is publicly viewable on GitHub.

For videos and blogs on data engineering and building your data stack, check out Airbyte's Content Hub, YouTube, and sign up for our newsletter.

Contributing

If you've found a problem with Airbyte, please open a GitHub issue. To contribute to Airbyte and see our Code of Conduct, please see the contributing guide. We have a list of good first issues that contain bugs that have a relatively limited scope. This is a great place to get started, gain experience, and get familiar with our contribution process.

PR Permission Requirements

When submitting a pull request, please ensure that Airbyte maintainers have write access to your branch. This allows us to apply formatting fixes and dependency updates directly, significantly speeding up the review and approval process.

To enable write access on your PR from Airbyte maintainers, please check the "Allow edits from maintainers" box when submitting from your PR. You must also create your PR from a fork in your personal GitHub account rather than an organization account, or else you will not see this option. The requirement to create from your personal fork is based on GitHub's additional security restrictions for PRs created from organization forks. For more information about the GitHub security model, please see the GitHub documentation page regarding PRs from forks.

For more details on contribution requirements, please see our contribution workflow documentation.

Security

Airbyte takes security issues very seriously. Please do not file GitHub issues or post on our public forum for security vulnerabilities. Email [email protected] if you believe you have uncovered a vulnerability. In the message, try to provide a description of the issue and ideally a way of reproducing it. The security team will get back to you as soon as possible.

Airbyte Enterprise also offers additional security features (among others) on top of Airbyte open-source.

License

See the LICENSE file for licensing information, and our FAQ for any questions you may have on that topic.

Thank You

Airbyte would not be possible without the support and assistance of other open-source tools and companies! Visit our thank you page to learn more about how we build Airbyte.

Frequently asked questions

Is Airbyte free to use?

Airbyte is open source. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does Airbyte do?

Open-source data integration for modern teams

What is Airbyte written in?

Airbyte is primarily written in Python. Its source is publicly available at https://github.com/airbytehq/airbyte, and it has 22,082 GitHub stars.