AWS Glue, Apache Airflow and Airbyte are often compared, but each does a different job. Glue is Amazon's serverless Spark service for transforming and cataloging data in AWS. Airflow is a free, open-source orchestrator that schedules tasks you write in Python. Airbyte is an open-source data movement platform with 700+ connectors that loads data into any destination. Many teams use two or all three together.
AWS Glue vs Airflow vs Airbyte at a glance
| AWS Glue | Apache Airflow | Airbyte |
|---|
| Category | Serverless Spark ETL and data catalog | Open-source workflow orchestration | Open data movement (ELT and CDC) |
| Core job | Transform and catalog data inside AWS | Schedule, chain and monitor tasks | Extract and load data from 700+ sources |
| Connectors | AWS-native sources, JDBC, plus selected SaaS and AWS Marketplace connectors | Provider operators and hooks; extract logic is yours to write | 700+ maintained connectors |
| Building pipelines | PySpark or Scala jobs, or Glue Studio | Python DAGs | Configure in UI, API, Terraform or PyAirbyte |
| Pricing model | $0.308 per DPU-hour on Glue 6.0, $0.44 on 5.1 and earlier (us-east-1) | Free (Apache 2.0); infrastructure and engineering time, or a managed provider | Free (Core); Cloud from $20/month; capacity-based Data Workers on Pro and Enterprise Flex |
| Deployment | AWS-managed only | Self-managed, or Astronomer, Amazon MWAA or Google Cloud Composer | Self-hosted, managed cloud, hybrid or fully on-prem |
| Destinations | Primarily AWS (S3, Redshift, SageMaker Lakehouse) | Anything your code can reach | Any warehouse, lakehouse, database or vector store, on any cloud |
| Current version | Glue 6.0 (August 2026) | Airflow 3.x (Airflow 2 reached end of life in April 2026) | Continuous releases |
| Open source | No | Yes | Yes |
About AWS Glue
AWS Glue is Amazon's serverless data integration service. It runs Apache Spark, Python shell and Ray jobs, catalogs data with crawlers and the Glue Data Catalog, and offers zero-ETL integrations into S3, Redshift and SageMaker Lakehouse. Glue 6.0 shipped in August 2026 with a newer Spark runtime, Apache Iceberg v3 support and 30% lower DPU rates.
About Apache Airflow
Apache Airflow is an open-source workflow orchestrator, originally built at Airbnb and now an Apache Software Foundation project. You define workflows as Python DAGs, and Airflow schedules, runs and monitors each task. Airflow 3 is the current major line; Airflow 2 reached end of life on April 22, 2026.
About Airbyte
Airbyte is the open standard for data movement, used by 18% of the Fortune 500. It replicates data from 700+ sources into warehouses, lakehouses, databases and AI context stores, and runs self-hosted, fully managed, or hybrid inside your own boundary.
Three different jobs
These tools cover three different layers of a data stack:
- Airbyte moves data. It extracts from SaaS apps, APIs, databases and files and loads into your destination, with incremental syncs, CDC and schema changes built in.
- Glue transforms data. It runs Spark jobs over data already in AWS and catalogs it for Athena, EMR and Redshift Spectrum.
- Airflow orchestrates. It decides when each step runs and in what order, but every task is code you write or a tool you call.
The overlap is ingestion. Glue and Airflow can both pull data from sources, but only by writing and maintaining that code yourself.
Pricing: compute time, free software or capacity
AWS Glue bills per DPU-hour, per second with a one-minute minimum. In us-east-1, Spark jobs cost $0.308 per DPU-hour on Glue 6.0 and $0.44 on Glue 5.1 and earlier. Crawlers, interactive sessions and data quality add DPU time, streaming jobs bill continuously, and zero-ETL application ingestion adds $1.50 per GB. Cost depends on how well each job is sized and tuned.
Airflow is free under the Apache 2.0 license. The cost is in running it: schedulers, workers and a metadata database, plus upgrades such as the move from Airflow 2 to 3. Amazon MWAA, Astronomer and Google Cloud Composer run it for you for a fee.
Airbyte Core is free to self-host. Cloud starts at $20/month (Standard) and $189/month (Plus). Pro and Enterprise Flex price on Data Workers, dedicated compute capacity, so cost doesn't depend on row counts or job tuning.
Connectors and ingestion
Airbyte ships 700+ maintained connectors, and its Connector Builder generates new ones from API docs with AI assist.
Glue's native connectors center on AWS services and JDBC databases, plus a set of SaaS and AWS Marketplace connectors. Other sources mean custom Spark code.
Airflow's provider packages give you operators and hooks, but a hook is a client, not a pipeline. For every source, your team still writes and maintains authentication, pagination, incremental state, schema handling and retries.
Glue is a transformation engine: it runs Spark at scale over S3 data lakes, and its Data Catalog is the default metastore for Athena, EMR and Redshift Spectrum.
Airflow doesn't transform data itself; it runs dbt models, SQL, Spark or Glue jobs on a schedule.
Airbyte focuses on data movement and integrates natively with dbt, Airflow, Dagster and Prefect for what happens next.
Deployment
Glue runs only in AWS and is designed around AWS destinations.
Airflow runs anywhere you can run Python, from Kubernetes to on-prem servers, or as a managed service like MWAA.
Airbyte runs four ways on one codebase: free self-hosted Core, managed cloud, hybrid, or fully on-prem with Enterprise Flex. It writes to S3, Redshift and Iceberg as well as Snowflake, BigQuery and Databricks, and can run inside your own AWS account.
When to choose AWS Glue, Airflow or Airbyte
| Your situation | Better fit |
|---|
| You run heavy Spark transformations on an S3 data lake | AWS Glue |
| You need a data catalog for Athena, EMR and Redshift Spectrum | AWS Glue |
| You orchestrate multi-step workflows across many tools | Airflow |
| You need free, open-source orchestration with full control in code | Airflow |
| You need SaaS, API or database data without writing ingestion code | Airbyte |
| Your Airflow DAGs or Glue jobs are mostly custom extract-and-load code | Airbyte |
| You load into non-AWS destinations, or several clouds | Airbyte |
| You need to self-host or run fully on-prem | Airbyte or Airflow |
Using them together
On AWS, a common stack uses all three: Airbyte loads SaaS and database data into S3, Redshift or Iceberg tables, Glue or dbt transforms it, and Airflow (often on MWAA) runs the sequence. The official Airbyte provider lets an Airflow DAG trigger a sync and wait for it to finish before the Glue job starts.
Related comparisons: Airbyte vs AWS Glue, Airbyte vs Airflow, Fivetran vs AWS Glue vs Airbyte, Apache NiFi vs Airflow vs Airbyte.
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