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airbytehq/airbyte

📈 Trending★ 21,282PythonAudience · dataComplexity · 4/5ActiveLicenseSetup · hard

TLDR

Open-source platform that moves data from APIs, databases, and files into warehouses and data lakes using 600+ pre-built connectors or custom ones you build.

Mindmap

mindmap
  root((Airbyte))
    What it does
      Extract from sources
      Load to destinations
      ELT pipelines
    Connectors
      600+ pre-built
      No-code builder
      Low-code SDK
    Deployment
      Self-hosted
      Airbyte Cloud
    Orchestration
      Airflow integration
      Dagster integration
      API access
    AI features
      Agent SDK
      Real-time data access
      LLM integration

Things people build with this

USE CASE 1

Sync customer data from Salesforce into your data warehouse daily without writing code.

USE CASE 2

Build a real-time data pipeline that feeds live CRM data to an AI agent for customer insights.

USE CASE 3

Move logs and events from your APIs into a data lake for analytics and reporting.

USE CASE 4

Create custom connectors for proprietary databases or internal APIs using the low-code SDK.

Tech stack

PythonAirflowDagsterKestraLangChainOpenAIFastMCP

Getting it running

Difficulty · hard Time to first run · 1day+

Requires orchestration engine (Airflow/Dagster/Kestra), data warehouse/lake setup, and connector configuration for end-to-end pipeline.

Use freely under MIT or Elastic License v2; enterprise features available for larger organizations.

In plain English

Airbyte is an open-source data movement platform designed to copy data from sources like APIs, databases, and files into destinations like data warehouses, data lakes, and databases. This kind of data pipeline is often called ELT (Extract, Load, Transform). Airbyte provides a catalog of 600+ pre-built connectors covering popular services and databases, and also lets you build new connectors using a no-code Connector Builder or a low-code SDK. It can be self-hosted (deployed on your own infrastructure) or used via Airbyte Cloud. Syncs can be orchestrated through integrations with tools like Airflow, Dagster, or Kestra, or via its own API. Beyond traditional data warehousing use cases, Airbyte also offers an Agent SDK that lets AI agents and LLM applications access live business data from CRMs, support tools, SaaS APIs, and databases in real time. The Agent SDK integrates with frameworks like LangChain, OpenAI Agents, pydantic-ai, and FastMCP. The project is MIT and Elastic License v2 licensed, has an active community on Slack, and its roadmap is publicly visible on GitHub. Enterprise features are available for larger organizations.

Copy-paste prompts

Prompt 1
How do I set up an Airbyte connector to sync data from Stripe to Snowflake?
Prompt 2
Show me how to build a custom connector using Airbyte's low-code SDK for my internal API.
Prompt 3
How can I use Airbyte's Agent SDK to let an LLM application query live Salesforce data?
Prompt 4
What's the best way to orchestrate Airbyte syncs using Apache Airflow?
Prompt 5
How do I self-host Airbyte on my own infrastructure instead of using the cloud version?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.