docs/platform/readme.md
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Use Airbyte's data replication platform to consolidate data from hundreds of sources into your data warehouses, data lakes, and databases. Then, move data into the operational tools where work happens, like CRMs, marketing platforms, and support systems.
Whether you're part of a large organization managing complex data pipelines or an individual analyst consolidating data, Airbyte works for you. Airbyte offers flexibility and scalability that's easy to tailor to your specific needs, from one-off jobs to enterprise solutions.
Teams and organizations need efficient and timely data access to an ever-growing list of data sources. In-house data pipelines are brittle and costly to build and maintain. Airbyte's unique open source approach enables your data stack to adapt as your data needs evolve.
Wide connector availability: Airbyte's connector catalog comes "out-of-the-box" with over 600 pre-built connectors. These connectors can be used to start replicating data from a source to a destination in just a few minutes.
Long-tail connector coverage: You can easily extend Airbyte's capability to support your custom use cases through Airbyte's No-Code Connector Builder.
Robust platform provides horizontal scaling required for large-scale data movement operations, available as Cloud-managed or Self-managed.
Accessible User Interfaces through the UI, PyAirbyte (Python library), API, and Terraform Provider to integrate with your preferred tooling and approach to infrastructure management.
Airbyte is suitable for a wide range of data integration use cases, including AI data infrastructure and EL(T) workloads.
Airbyte's data replication platform is an extract, load, and data activation solution. You might know this as ELT/reverse ETL.
Data replication is ideal when you:
Data replication isn't ideal when you:
Airbyte's data replication platform is available as a self-managed, hybrid, or fully managed cloud solution.
Once your Airbyte instance is up and running, there's a way to use Airbyte that's appropriate for any skill level.
Self-managed and cloud plans come with a carefully crafted user interface that walks you through setting up connections and automating syncs. This is a great choice if you're not a developer, aren't concerned about version control, or you're just seeing what Airbyte can do for you.
These are great choices for developers who want to automate the way you work with Airbyte and use version control to preserve a history of changes.
Many people think of Airbyte and its connectors as infrastructure. The Terraform provider ensures you can deploy and manage sources and destinations with Terraform, the same way you manage your other infrastructure today.
If you want to use Python to move data, our Python library, PyAirbyte, might be the best fit for you. It's a good choice if you're using Jupyter Notebook or iterating on an early prototype for a large data project and don't need to run a server. PyAirbyte isn't an SDK for managing Airbyte. If that's what you're looking for, use the API or Python SDK.
Airbyte is an open source product. This is vital to Airbyte's vision of data movement. The world has seemingly infinite data sources, and only through community collaboration can we address that long tail of data sources.
If you don't see the data source you need in Airbyte's collection, you can build one. Airbyte comes with no-code, low-code, and programmatic builder options. If you're interested in giving back to the community, documenting your connector and publishing it in the Marketplace will help others like you move data in the future.