AWS Certified Machine Learning – SpecialtyData EngineeringEasy

A data engineering team is building a serverless data lake. They ingest data from various sources into Amazon S3. To enable efficient querying by services like Amazon Athena and Amazon Redshift Spectrum, they need a centralized metadata repository that automatically discovers schema and partitions. They also require the ability to define and enforce fine-grained access control on tables and columns without managing separate databases. Which AWS service is purpose-built to meet these requirements?

  1. AAmazon DynamoDB
  2. BAmazon EMR Metastore
  3. CAWS Glue Data Catalog
  4. DAmazon RDS
Show answer & explanation

Correct answer: C. AWS Glue Data Catalog

The AWS Glue Data Catalog is a fully managed, centralized metadata repository for all your data assets, including those in S3. It automatically discovers schemas and partitions using crawlers and allows for fine-grained access control through AWS Lake Formation, making it ideal for serverless data lakes and integration with Athena/Redshift Spectrum.

Why the other options are wrong

  • A. Amazon DynamoDB is a NoSQL database, not a metadata catalog for S3 data lakes.
  • B. Amazon EMR Metastore can be used with EMR, but it is not a fully managed, serverless, centralized catalog for a broader data lake architecture that integrates with services like Athena without an active EMR cluster.
  • D. Amazon RDS is a relational database service, not suitable as a metadata catalog for S3 data lakes.

AWS Glue Data Catalog

A persistent, metadata store for data assets in your data lake, providing schema, table, and partition information for various AWS analytics services.

  • Fully managed and serverless.
  • Automatically discovers schema and partitions using crawlers.
  • Integrates with Amazon Athena, Redshift Spectrum, EMR, and AWS Lake Formation.
  • Enables fine-grained access control via Lake Formation.

Memory trick: Glue Catalog knows all, for Athena and Redshift, it's the central hall!

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