Feature-level notice: AWS Glue Ray jobs have been closed to new customers since April 30, 2026. The remaining Glue capabilities, including Spark-based ETL jobs and the Data Catalog, are not affected.
What is AWS Glue?
AWS Glue is a serverless data integration service that makes discovering, preparing, and combining data from diverse sources simpler, faster, and cheaper. Glue comprises several components: the Data Catalog as a central metadata repository, ETL functionality for building and running data pipelines, AWS Glue Studio for visual pipeline development, and interactive sessions for exploratory data preparation in IDEs or notebooks.
Core Features
- Data Catalog: Central metadata repository for tables and schemas, compatible with Athena, Redshift, and EMR
- Glue Crawlers: Automatic scanning of data sources and schema detection for S3, RDS, and JDBC databases
- Glue ETL: Serverless Spark-based transformations in Python or Scala
- Glue Studio: Visual editor for graphically building ETL pipelines
- Interactive Sessions: Exploratory data preparation directly in IDEs or notebooks
- Glue DataBrew: No-code data preparation with pre-built transformations for data analysts and data scientists
Typical Use Cases
Data Lake Construction
Glue Crawlers scan various data sources and create a unified catalog. ETL jobs transform raw data into analyzable formats like Parquet and load them into S3-based data lakes.
Data Warehouse Integration
Data from operational systems is transformed and loaded into Amazon Redshift. Glue handles schema mapping, data type conversion, and incremental loads.
Machine Learning Data Preparation
DataBrew cleans and normalizes data for ML workflows. Missing values are handled, outliers detected, and features prepared for training.
Benefits
- No infrastructure management: automatic scaling of the underlying Spark clusters
- Pay-per-use billing by DPU hours
- Integration with the entire AWS analytics stack
- Reusable transformations and job bookmarks for incremental processing
Integration with innFactory
As an AWS Reseller, innFactory supports you with AWS Glue: building data lake architectures, developing ETL pipelines in Python/Scala, and integration with existing data warehouse systems.
Typical Use Cases
Frequently Asked Questions
What is AWS Glue?
AWS Glue is a serverless data integration service (ETL: Extract, Transform, Load). It automates discovering, preparing, and combining data from AWS, on-premises, and other cloud sources for analytics and machine learning.
What is the AWS Glue Data Catalog?
The Data Catalog is a central metadata repository that manages table and schema information about your data sources. It is compatible with Athena, Redshift Spectrum, and EMR, providing a unified view of data from different sources.
What is AWS Glue DataBrew used for?
Glue DataBrew is a visual, no-code data preparation tool for data analysts and data scientists. It enables cleaning and normalizing data through pre-built transformations without writing code, for example to prepare training data for machine learning.
What does AWS Glue cost?
AWS Glue is billed based on DPU hours (Data Processing Units) used for ETL jobs and crawlers, with additional costs for the Data Catalog and optional components like DataBrew. There are no minimum fees; see the official pricing page for exact rates.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of AWS (official documentation). This page does not represent an offer by AWS.