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What's the Difference Between AWS Data Pipeline and AWS Glue DataBrew?

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

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Comparisons
AWS Data Pipeline
AWS Glue DataBrew
Category

Analytics, Data integration / ETL

Analytics, Data Preparation
Description

Process and move data between different AWS compute and storage services on a scheduled basis.

Visual data preparation tool for cleaning and normalizing data without writing code.
Best for
  • Scheduled data movement
  • ETL workflows
  • Cross-region data copy
  • Data backups
  • Data cleaning
  • Data normalization
  • Data profiling
  • Feature engineering
Key features
  • Scheduling
  • Retry logic
  • Dependency tracking
  • On-premises support
  • Multiple data sources
  • 250+ transformations
  • Visual interface
  • Data profiling
  • Recipe jobs
  • S3/Redshift/RDS sources
Pricing model

Pay per activity and precondition

Pay per DataBrew session + node hours
Free tier

—

Yes
Expert take

“Data Pipeline orchestrates data movement between AWS services on a schedule. For new workloads, Step Functions or Glue workflows are more modern alternatives.”
— Gary McLean, re:Post Top Contributor [profile]

“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]
Product page

Learn more about AWS Data Pipeline »

Learn more about AWS Glue DataBrew »

When to use AWS Data Pipeline or AWS Glue DataBrew

Use AWS Data Pipeline when:

  • Scheduled data movement
  • ETL workflows
  • Cross-region data copy
  • Data backups

Learn more about AWS Data Pipeline »

Use AWS Glue DataBrew when:

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

Learn more about AWS Glue DataBrew »

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