Automated crawlers
Scan data sources and infer schemas without building tables by hand.
AWS Glue
Serverless data integration service to discover, catalog, prepare, and move data for analytics.
Data IntegrationETLData CatalogServerless Data
Overview
What is AWS Glue?
AWS Glue is a serverless data integration service from Amazon Web Services for discovering, preparing, and combining data for analytics, machine learning, and application development. Crawlers scan sources and infer schemas into a central Data Catalog, while Spark-based ETL jobs transform and move data between stores. It connects to more than 100 sources and scales automatically. Data engineers, developers, and analytics teams use AWS Glue to build pipelines without managing infrastructure.
Data EngineersCloud DevelopersAnalytics TeamsDevOps EngineersAWS Users
Product snapshot
- Category
- Data Discovery & Exploration
- Best for
- Serverless ETL on AWS
- Deployment
- Cloud
- Free trial
- No
- Integrations
- S3, Redshift, Athena, EMR
- AI features
- Yes
Key features
Key features of AWS Glue
Reviews
AWS Glue reviews
Haniel L.
Software Development Engineer II
“Liked moving data between databases and services such as S3, plus the built-in Spark code editor. Found it gets complicated quickly, can be expensive, and permission issues are hard to debug.”
Verified Reviewer
Software Engineer
“Liked not having to manage servers, scaling, or infrastructure for ETL work. Found the pre-built templates limit how much jobs can be customized.”
David W.
Head of Engineering
“Liked the broad functionality and how well it works with other AWS products. Found it hard to set up and debug, with much of its power missing from the GUI.”
Verified Reviewer
Senior Data Engineer
“Liked how well the crawler scans source files and runs initial validations. Found the scheduler lacking in features, with no way to set job dependencies.”
Angel C.
Employee
“Liked how powerful it is for data analysis, integration, and cleaning, saving significant time on data work. Noted no major drawbacks with the service.”
Mia G.
Associate Software Engineer
“Liked how easily it integrates many data sources, using it to move data from S3 to Redshift. Found the initial setup complex and configuring permissions slow.”
Zie Mamadou C.
Application Developer
“Liked connecting to multiple data sources through a managed Amazon ETL service. Found it complex to use, with dependence on Amazon and high deployment costs.”
Parth P.
DevOps Engineer
“Liked the serverless model, ease of learning, and how quickly pipelines run. Found the cluster startup time longer than it should be.”
Anis B.
Software Developer
“Liked the easy setup and integration with AWS tools, plus simple monitoring and dashboards. Found data consumption rates hard to manage and that it handles only batch, not real-time, data.”
Laura R.
Database Engineer
“Liked that it is easy to use, well documented, and reasonably priced. Found it too simplistic for complex transformations, which it handles poorly.”
Alternatives
Top AWS Glue alternatives
Azure Data Factory
Best forAzure data pipelines
Why choose itManaged ETL with visual pipeline design
Fivetran
Best forManaged data replication
Why choose itPrebuilt connectors with minimal pipeline upkeep
Talend
Best forData integration and quality
Why choose itOpen data integration with quality tools
Google Cloud Dataflow
Best forGoogle Cloud pipelines
Why choose itUnified batch and streaming data processing
Integrations
AWS Glue integrations
FAQ