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How to Build a Serverless Data Lake on AWS Using S3, Glue, and Athena

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A technical guide published on DEV Community outlines the core AWS services required to build a fully serverless Data Lake. The architecture rests on five pillars — storage, processing, catalog, security, and consumption — with Amazon S3 serving as the foundational layer for both raw and processed data. AWS Glue handles schema discovery and ETL transformations using PySpark-based jobs, while the Glue Catalog acts as a centralized metadata store for all datasets. Amazon Athena enables standard SQL querying directly against S3 data without provisioning any servers, operating on a pay-per-query model. The guide recommends a single S3 bucket with a structured folder hierarchy following bronze, silver, and gold data tiers to optimize both cost and performance.

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How to Build a Serverless Data Lake on AWS Using S3, Glue, and Athena · ShortSingh