What is AWS Glue?
AWS Glue is a serverless ETL (Extract, Transform, Load) service for data integration. The service automates discovering, preparing, and combining data for analytics and machine learning. Glue consists of three main components: Data Catalog, ETL Engine, and Glue Studio for visual ETL development.
Core Features
- Data Catalog: Central metadata repository that automatically detects schemas and is 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 ETL editor for drag-and-drop pipeline development
- Glue DataBrew: No-code data preparation with over 250 pre-built transformations
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 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.