AWS Glue Review 2026

AWS Glue is a serverless data integration service for discovering, preparing, and combining data for analytics, machine learning, and application development. It supports ETL workflows, data cataloging, and scalable data processing on AWS.

AWS Glue is a fully managed, serverless data integration service provided by Amazon Web Services that enables organizations to discover, prepare, move, and combine data from multiple sources for analytics, machine learning, and application development. It eliminates the need to provision or manage infrastructure for ETL (Extract, Transform, Load) pipelines, allowing data engineers and analysts to focus on transformation logic rather than cluster management.

At its core, AWS Glue provides several integrated components. The Glue Data Catalog serves as a centralized, persistent metadata repository compatible with Apache Hive Metastore, storing table definitions, schemas, and partition information for data assets across S3, RDS, Redshift, and dozens of other data stores. Glue Crawlers automatically scan data sources, infer schemas, and populate the Data Catalog, reducing manual cataloging effort. Glue ETL Jobs run on a managed Apache Spark or Apache Ray environment, supporting Python (PySpark) and Scala for batch transformations, with auto-scaling that adjusts Data Processing Units (DPUs) based on workload. As of Glue version 4.0, jobs run on an optimized Spark 3.3.0 runtime with up to 2.7x faster start times and improved performance over earlier versions.