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What's the Difference Between AWS Glue and Glue Elastic Views?

Compare AWS Glue and Glue Elastic Views side by side — features, pricing, and ideal use cases to help you choose the right product.

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AWS Glue
Glue Elastic Views
Category

Analytics, Data integration / ETL

Analytics, Data integration / ETL
Description

Simple, scalable, and serverless data integration

Build materialized views that automatically combine and replicate data across multiple data stores.
Best for
  • ETL
  • Data cataloging
  • Data preparation
  • Data lake management
  • Event-driven ETL
  • Cross-store data replication
  • Materialized views
  • Data synchronization
  • Real-time data access
Key features
  • Data Catalog
  • ETL engine
  • Crawlers
  • Job bookmarks
  • DataBrew
  • SQL-based views
  • Automatic replication
  • Multiple target stores
  • Change data capture
  • Monitoring
Pricing model

Pay per DPU-hour

Pay per vCPU-hour for replication
Free tier

Yes

—
Expert take

“Glue Data Catalog is the metadata backbone for Athena, Redshift Spectrum, and EMR; it tells them where data lives and what it looks like. The ETL engine runs Spark under the hood but with serverless scaling. Use crawlers to auto-discover schemas and partitions in S3.”
— Giovanni Lauria, re:Post Top Contributor [profile]

“Glue Elastic Views replicates data across AWS data stores automatically. Define a view once and it materializes in DynamoDB, S3, Redshift, or OpenSearch without ETL pipelines.”
— Didier Durand, re:Post Top Contributor [profile]
Product page

Learn more about AWS Glue »

Learn more about Glue Elastic Views »

When to use AWS Glue or Glue Elastic Views

Use AWS Glue when:

  • ETL
  • Data cataloging
  • Data preparation
  • Data lake management
  • Event-driven ETL

Learn more about AWS Glue »

Use AWS Glue Elastic Views when:

  • Cross-store data replication
  • Materialized views
  • Data synchronization
  • Real-time data access

Learn more about Glue Elastic Views »

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