Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue
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This article provides a comprehensive guide for migrating SQL-based ETL workloads to AWS Glue serverless infrastructure.
- AWS Glue enables serverless ETL with on-demand scaling using Spark SQL
- AWS DMS replicates data from Aurora to S3 with Change Data Capture support
- AWS Glue crawlers automatically infer schema and populate the Data Catalog
- SQL queries transform data across multiple tables without coding
- AWS Glue Studio provides visual interface for creating and monitoring ETL jobs
- Solution uses Amazon Redshift as data warehouse for fact and dimension tables
- CloudFormation template automates environment setup in 25-30 minutes
- Jobs can be scheduled using AWS Glue workflows for ongoing data movement
This solution demonstrates migrating transactional data from Aurora through S3 to Redshift using serverless AWS services, minimizing refactoring effort for SQL-based ETL workloads.
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