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

Compare AWS Data Pipeline and AWS Glue 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
Category

Analytics, Data integration / ETL

Analytics, Data integration / ETL
Description

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

Simple, scalable, and serverless data integration
Best for
  • Scheduled data movement
  • ETL workflows
  • Cross-region data copy
  • Data backups
  • ETL
  • Data cataloging
  • Data preparation
  • Data lake management
  • Event-driven ETL
Key features
  • Scheduling
  • Retry logic
  • Dependency tracking
  • On-premises support
  • Multiple data sources
  • Data Catalog
  • ETL engine
  • Crawlers
  • Job bookmarks
  • DataBrew
Pricing model

Pay per activity and precondition

Pay per DPU-hour
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 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]
Product page

Learn more about AWS Data Pipeline »

Learn more about AWS Glue »

When to use AWS Data Pipeline or AWS Glue

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 when:

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

Learn more about AWS Glue »

AWS product comparisons

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