ELT & data integration · Amazon Web Services

AWS Glue

Serverless AWS ETL service using Apache Spark under the hood, billed per Data Processing Unit-hour with no infrastructure to manage.

Visit AWS Glue Alternatives

AWS Glue is a serverless data integration service for discovering, cataloging and transforming data across AWS and external sources. Its Data Catalog acts as a persistent, Hive-compatible metadata store shared by other AWS analytics services (Athena, Redshift Spectrum, EMR); Crawlers populate it automatically from S3, JDBC or other sources. ETL jobs run on managed Apache Spark or Python shell environments without provisioning clusters, and Glue Studio provides a visual, drag-and-drop job authoring interface alongside a code-first option. Because it bills per Data Processing Unit-hour (DPU-hour) rather than a fixed subscription, cost scales directly with job runtime and parallelism, which suits variable or bursty batch workloads more than steady, high-frequency pipelines where a flat-fee tool may be cheaper.

At a glance

Vendor Amazon Web Services
Pricing model Usage-based
Free tier Yes
Deployment Cloud
Open source No
Best for AWS-native teams needing serverless, pay-per-use ETL and a shared metadata catalog across analytics services.

Pricing

Billed per Data Processing Unit-hour (DPU-hour) for ETL jobs and crawlers, by the second; Data Catalog storage and requests are free up to the first million objects/accesses monthly.

Plan Price Notes
ETL jobs & crawlers $0.44 per DPU-hour Billed per second, with a minimum job duration; rate varies by AWS Region
Data Catalog Free for first 1M objects and 1M requests/month $1.00 per 100,000 objects and $1.00 per million requests beyond the free tier
DataBrew $1.00 per 30-min interactive session; $0.48 per node-hour for jobs Visual data preparation add-on

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

Features

  • Serverless Apache Spark and Python ETL jobs
  • Auto-populated Hive-compatible Data Catalog
  • Crawlers for automatic schema discovery
  • Visual job authoring via Glue Studio
  • Zero-ETL integrations with other AWS services
  • Glue DataBrew for no-code data preparation
  • Schema Registry for streaming data

Integrations

Profile last reviewed September 21, 2026

Alternatives

Azure Data Factory Microsoft's cloud ETL/ELT and orchestration service for building and scheduling data pipelines across Azure and hybrid sources. Google Cloud Dataflow Fully managed, serverless service for running unified batch and streaming data pipelines built on Apache Beam. Matillion Cloud-native ELT platform with a low-code visual pipeline designer that pushes transformations down into the target warehouse. Talend Enterprise data integration and data quality suite, now sold as Qlik Talend Cloud after Qlik's acquisition of Talend.

AWS Glue in the index now

Terms to know

ETL (extract, transform, load) A data integration pattern that transforms data before loading it, unlike ELT which transforms after loading. ELT (extract, load, transform) A data integration pattern that loads raw data first and transforms it afterward using the warehouse's own compute. Data catalog A searchable inventory of an organization's data assets, with descriptions, ownership and usage attached. Data pipeline The automated sequence of steps that moves data from source systems to a destination, transforming it along the way. Apache Spark An open-source distributed computing engine for processing large datasets in parallel across a cluster of machines.

Related guides

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.