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

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

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Comparisons
AWS Glue DataBrew
Glue Elastic Views
Category

Analytics, Data Preparation

Analytics, Data integration / ETL
Description

Visual data preparation tool for cleaning and normalizing data without writing code.

Build materialized views that automatically combine and replicate data across multiple data stores.
Best for
  • Data cleaning
  • Data normalization
  • Data profiling
  • Feature engineering
  • Cross-store data replication
  • Materialized views
  • Data synchronization
  • Real-time data access
Key features
  • 250+ transformations
  • Visual interface
  • Data profiling
  • Recipe jobs
  • S3/Redshift/RDS sources
  • SQL-based views
  • Automatic replication
  • Multiple target stores
  • Change data capture
  • Monitoring
Pricing model

Pay per DataBrew session + node hours

Pay per vCPU-hour for replication
Free tier

Yes

—
Expert take

“Glue DataBrew provides a visual interface for data cleaning and normalization with 250+ built-in transformations. It generates profile reports that highlight data quality issues.”
— Didier Durand, 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 DataBrew »

Learn more about  Glue Elastic Views »

When to use AWS Glue DataBrew or Glue Elastic Views

Use AWS Glue DataBrew when:

  • Data cleaning
  • Data normalization
  • Data profiling
  • Feature engineering

Learn more about AWS Glue DataBrew »

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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