What is AWS Glue, and how is it used for ETL?

I-Hub Talent is the best Full Stack AWS with Data Engineering Training Institute in Hyderabad, offering comprehensive training for aspiring data engineers. With a focus on AWS and Data Engineering, our institute provides in-depth knowledge and hands-on experience in managing and processing large-scale data on the cloud. Our expert trainers guide students through a wide array of AWS services like Amazon S3, AWS Glue, Amazon Redshift, EMR, Kinesis, and Lambda, helping them build expertise in building scalable, reliable data pipelines.

At I-Hub Talent, we understand the importance of real-world experience in today’s competitive job market. Our AWS with Data Engineering training covers everything from data storage to real-time analytics, equipping students with the skills to handle complex data challenges. Whether you're looking to master ETL processes, data lakes, or cloud data warehouses, our curriculum ensures you're industry-ready.

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AWS Glue is a fully managed Extract, Transform, Load (ETL) service provided by Amazon Web Services that simplifies the process of preparing and moving data for analytics, machine learning, and application development. It automates much of the effort involved in data integration, making it easier to discover, catalog, clean, enrich, and transform data across various data sources.

AWS Glue consists of several key components:

  1. Data Catalog: A central metadata repository that stores table definitions, job metadata, and other control information used during ETL operations.

  2. Crawlers: These scan data sources (like Amazon S3, RDS, or Redshift) and automatically populate the Data Catalog with metadata.

  3. ETL Jobs: Code-based or visual workflows (using Glue Studio) that define how data is extracted, transformed, and loaded into target systems. Glue jobs are typically written in Python or Scala using Apache Spark under the hood.

  4. Triggers and Workflows: Used to automate and orchestrate ETL jobs based on events or schedules.

How it's used for ETL:

  • Extract: Connects to structured and unstructured data sources (e.g., S3, JDBC databases) to retrieve raw data.

  • Transform: Performs operations like filtering, mapping, joining, and format conversion using built-in or custom transformations.

  • Load: Writes the transformed data to destinations like Amazon Redshift, S3, or other data warehouses and lakes.

AWS Glue is ideal for building scalable, serverless ETL pipelines with minimal infrastructure management.

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