Skip to main content

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

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

Compare side-by-side

Comparisons
AWS Data Pipeline
Glue Elastic Views
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.

Build materialized views that automatically combine and replicate data across multiple data stores.
Best for
  • Scheduled data movement
  • ETL workflows
  • Cross-region data copy
  • Data backups
  • Cross-store data replication
  • Materialized views
  • Data synchronization
  • Real-time data access
Key features
  • Scheduling
  • Retry logic
  • Dependency tracking
  • On-premises support
  • Multiple data sources
  • SQL-based views
  • Automatic replication
  • Multiple target stores
  • Change data capture
  • Monitoring
Pricing model

Pay per activity and precondition

Pay per vCPU-hour for replication
Expert take

“AWS 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]

“AWS 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 Data Pipeline »

Learn more about AWS Glue Elastic Views »

When to use AWS Data Pipeline or AWS Glue Elastic Views

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 Elastic Views when:

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

Learn more about AWS Glue Elastic Views »

AWS product comparisons

Read about AWS products side-by-side

Displaying 1-8 (21)
2026-07-30

What's the difference between Amazon Aurora and Amazon Neptune?

Both are purpose-built, fully managed AWS databases, but they solve fundamentally different problems. Aurora handles structured relational data with SQL; Neptune handles highly connected data where relationships between entities are the primary query pattern.
Learn more
2026-07-30

What's the difference between Amazon RDS and Amazon Redshift?

Both run SQL queries, but they're optimized for fundamentally different workloads. RDS handles transactional operations (inserts, updates, lookups) for your application. Redshift handles analytical queries (aggregations, scans, joins across billions of rows) for your data team.
Learn more
2026-07-30

What's the difference between Amazon Aurora and Amazon DynamoDB?

Both are fully managed AWS database services, but they serve fundamentally different data models and access patterns. Aurora is a relational database for structured data with relationships; DynamoDB is a NoSQL key-value store built for single-digit millisecond performance at any scale.
Learn more
2026-07-30

What's the difference between Amazon DocumentDB and Amazon Neptune?

Both handle semi-structured data, but they're optimized for different query patterns. DocumentDB stores and queries JSON documents; Neptune stores and traverses relationships between entities.
Learn more
2026-07-30

What are the differences between Amazon DynamoDB and Amazon DocumentDB?

Both are fully managed NoSQL databases on AWS, but they serve different data models. DynamoDB is a key-value store optimized for known access patterns at massive scale; DocumentDB is a document database for flexible JSON schemas with MongoDB compatibility.
Learn more
2026-07-30

What's the difference between Amazon DynamoDB and Amazon Keyspaces?

Both are fully managed, serverless-capable NoSQL databases on AWS. DynamoDB is AWS-native with its own API and data model; Keyspaces is Apache Cassandra-compatible, letting you use existing Cassandra drivers, tools, and expertise.
Learn more
2026-07-30

What's the difference between Amazon ElastiCache and Amazon MemoryDB?

Both are Redis-compatible, fully managed in-memory services on AWS. ElastiCache is designed as a caching layer in front of another database; MemoryDB is designed as a primary database that combines in-memory speed with Multi-AZ durability.
Learn more
2026-07-30

What's the difference between Amazon Aurora and Amazon RDS?

Both are fully managed relational database services on AWS, but Aurora is a cloud-native engine built for higher performance and availability, while RDS gives you familiar open-source and commercial engines with less operational overhead than self-managed.
Learn more

Did you find what you were looking for today?

Let us know so we can improve the quality of the content on our pages