ELT & data integration · Airbyte, Inc.

Airbyte

Open-source data movement platform with 600+ connectors, run self-hosted for free or as managed Airbyte Cloud.

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Airbyte is an open-source ELT platform built around the Airbyte Protocol, with a catalog of 600+ community and Airbyte-maintained connectors plus a low-code Connector Builder for writing custom ones. The open-source core (Airbyte Core / Airbyte OSS) can be self-hosted on Docker or Kubernetes at no cost, giving full control over infrastructure and data residency; Airbyte Cloud is the managed equivalent, adding orchestration, scaling and support on top of the same connector catalog. It supports log-based CDC for databases, a Python library (PyAirbyte) for loading data directly into dataframes, and change-data pipelines feeding warehouses like Snowflake or BigQuery. It sits alongside Fivetran and Meltano as an alternative for teams weighing openness and self-hosting against a fully managed service.

At a glance

Vendor Airbyte, Inc.
Pricing model Usage-based
Free tier Yes
Deployment Cloud, Self-hosted
Open source Yes (MIT)
Best for Teams wanting an open-source ELT platform they can self-host for data control, or run as managed cloud, with a broad long-tail connector catalog.

Pricing

Airbyte Core is free and open source to self-host; Airbyte Cloud bills by credits consumed, with a 30-day trial and several volume-based and capacity-based plans.

Plan Price Notes
Standard From $20/month Includes 5 credits, volume-based, additional credits $5 each; 30-day trial with 400 credits
Plus From $189/month for 40 credits Fixed credit packages from 40 to 2,000 credits ($189–$4,999/month); overage $5/credit
Pro Capacity-based, contact sales Priced on Data Workers rather than volume; premium support
Enterprise Flex Capacity-based, contact sales Data movement inside the customer's own cloud boundary; hybrid/on-prem options

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • 600+ pre-built and community connectors
  • Low-code and no-code Connector Builder
  • Log-based CDC for major databases
  • PyAirbyte for programmatic pipelines
  • Self-hostable on Docker or Kubernetes
  • dbt-based post-load transformations
  • Credit-based usage billing on Cloud

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

Fivetran Managed ELT platform with 700+ prebuilt connectors that automatically syncs source data into a cloud warehouse or lake. Meltano Open-source, code-first ELT framework built on the Singer specification, with an optional managed Meltano Cloud. Estuary Flow Real-time data integration platform that unifies batch ELT and streaming CDC pipelines with sub-second latency. Hevo Data No-code, fully managed ELT platform billed by monthly event volume, with 150+ connectors and near real-time sync.

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Terms to know

ELT (extract, load, transform) A data integration pattern that loads raw data first and transforms it afterward using the warehouse's own compute. ETL (extract, transform, load) A data integration pattern that transforms data before loading it, unlike ELT which transforms after loading. Data pipeline The automated sequence of steps that moves data from source systems to a destination, transforming it along the way. Change data capture (CDC) A technique for detecting and streaming only the rows that changed in a source system, instead of reloading everything. Data residency The requirement or practice of storing and processing data within a specific country or region's physical or legal boundaries.

Related guides

How to build a modern data stack Ingestion, warehouse, transformation, BI and activation — what a data stack needs at each company stage, and what to defer. How to choose an ELT tool ELT tools differ less on connector count than on who operates them, how pricing scales, and whether transformation happens in the tool or downstream. How to decide build vs buy for analytics A framework for the build-vs-buy decision in analytics infrastructure — total cost, maintenance burden and lock-in, layer by layer.