AWS Glue Documentation

Learn about AWS Glue features, how to get started, and how to access AWS Glue.

Learn about the AWS Glue Data Catalog, which is your persistent metadata store.

Use this tutorial to create your first AWS Glue Data Catalog, which uses an Amazon S3 bucket as your data source.

Populate the AWS Glue Data Catalog with metadata tables from data stores that you define.

Use AWS Glue connections to access certain types of data stores.

Create jobs through AWS Glue Studio, a graphical interface that makes it easy to create, run, and monitor integration jobs.

Write an AWS Glue extract, transform, and load (ETL) script through this tutorial to understand how to use scripts when you're building AWS Glue jobs.

Author interactive jobs in a notebook interface based on Jupyter notebooks in AWS Glue Studio.

Programmatically build and test scripts for data preparation using interactive sessions.

Start crawlers or AWS Glue jobs with event-based triggers. You can also design a chain of dependent jobs and crawlers.

Run your AWS Glue jobs, and then monitor them with automated monitoring tools, the Apache Spark UI, AWS Glue job run insights, and AWS CloudTrail.

Define workflows for ETL and integration activities for multiple crawlers, jobs, and triggers.

Provides a conceptual overview of AWS Glue, detailed instructions for using the various features, and a complete API reference for developers.

Describes the AWS CLI commands that you can use with AWS Glue.

Describes how to prepare data visually with ready-made data transformations for analytics and machine learning. Also provides an API reference complete with instructions, syntax, and examples.