Airbyte vs AWS Glue

Updated November 2026 · AppBreakup editorial

Airbyte

Open-source data movement platform with hundreds of connectors, self-hosted or in the cloud.

Open sourceSelf-hostable

Visit Airbyte Airbyte profile

AWS Glue

AWS's serverless ETL service with a central data catalog and Spark-based jobs.

Paid

Visit AWS Glue AWS Glue profile

The short answer

Airbyte suits data engineers who want open-source ELT with 700+ connectors, the option to self-host for free, and easy custom connectors. AWS Glue suits teams whose data lake or warehouse already lives on AWS and who want serverless Spark ETL plus a shared Data Catalog. The biggest difference is connector-led data movement from anywhere versus Spark-based transformation inside AWS.

Airbyte or AWS Glue: our take

Airbyte focuses on moving data from APIs, databases and files into warehouses, lakes and other destinations. Its core engine and connectors are open source, and a low-code Connector Builder and Python CDK make it practical to add sources no vendor supports. AWS Glue focuses on preparing data inside AWS. Its Data Catalog stores table definitions that Athena, Redshift and EMR can query, crawlers fill that catalog automatically, and transformation jobs run on managed Apache Spark or as small Python shell jobs. Glue Studio can build pipelines visually and generate editable code, and Glue adds data quality rules and streaming ETL. It connects to 70+ data sources, far fewer ready-made SaaS connectors than Airbyte's 700+.

Hosting and pricing follow from that. Airbyte Core is free to self-host with no row-based fees, though you then own upgrades, scaling and failed syncs; the managed cloud starts at $20/month with a 14-day trial and no credit card, and hybrid and on-premises plans exist for data that can't leave your environment. Glue is serverless and only runs on AWS. ETL is billed at $0.44 per DPU-hour, metered per second with a 1-minute minimum on Glue 2.0+, where one DPU is 4 vCPU and 16 GB memory. The Data Catalog includes 1M objects and 1M requests per month free.

Each has its own friction. Airbyte's community connectors vary in quality, and SSO and faster sync schedules sit on higher paid plans. Glue's Spark jobs need tuning and can be slow to start, and it offers little value off AWS.

The two can also work together: Airbyte to pull SaaS and database data into S3, Glue to catalog and transform it. Pick Airbyte if you need many connectors, want open source or self-hosting, or must build custom sources. Pick AWS Glue if your platform is on AWS and your main need is Spark transformations and a central catalog.

Choose Airbyte if…

Data engineers who want open-source ELT they can self-host and extend with custom connectors
You want open-source software
You need to host it on your own servers
You want a free option (AWS Glue is paid only)
You need Self-hosted, which AWS Glue doesn't list

Choose AWS Glue if…

Data engineers building Spark-based ETL and a data catalog for an AWS data lake or warehouse
Serverless Spark jobs with no cluster to run
Central Data Catalog shared by Athena, Redshift and EMR

What is Airbyte?

Airbyte moves data from APIs, databases and files into warehouses, lakes and other destinations. Its core engine and connectors are open source and free to run on your own servers, while Airbyte also sells a managed cloud with hosting, upgrades and support, plus hybrid and on-premises plans for companies whose data can't leave their environment. A low-code Connector Builder and a Python CDK make it practical to add sources that no vendor supports, which is a common reason teams choose it over closed services. Newer releases also expose data to AI agents through an MCP server. It is aimed at data engineers comfortable running infrastructure, though the cloud plans remove most of that work. Cloud pricing is credit-based with a monthly starting tier and a no-card trial. Self-hosting is free but means you own upgrades, scaling and connector failures.

What is AWS Glue?

AWS Glue is Amazon's serverless data integration service for moving and reshaping data inside AWS. Its Data Catalog stores table definitions that Athena, Redshift and EMR can query, and crawlers can scan data in S3 and databases to fill that catalog automatically. Transformation jobs run on a managed Apache Spark engine or as small Python shell jobs; you write the code yourself, use notebooks with interactive sessions, or build pipelines visually in Glue Studio, which generates the script for you. It also offers data quality rules, streaming ETL, schedulers and triggers, and connections to more than 70 data sources. There are no servers or clusters to manage, and it fits data engineers whose warehouse or lake already lives on AWS. Billing is by Data Processing Unit hours, metered per second with a short minimum; the Data Catalog has a monthly free allowance for metadata storage and requests. The trade-offs are Spark tuning, slow job start-ups compared with always-on clusters, and limited use outside AWS. It is managed through the AWS console, CLI and APIs.

Side by side

Attribute	Airbyte	AWS Glue
Pricing	Open source	Paid
Open source	Yes	No
Self-hostable	Yes	No
Platforms	Web, Self-hosted	Web
Best for	Data engineers who want open-source ELT they can self-host and extend with custom connectors	Data engineers building Spark-based ETL and a data catalog for an AWS data lake or warehouse
Status	Active	Active