Microsoft Azure Synapse vs Amazon Redshift

Developers should use Azure Synapse when building enterprise-scale data analytics solutions that require seamless integration between data warehousing and big data processing meets developers should learn and use amazon redshift when building data warehousing solutions that require fast query performance on large volumes of structured and semi-structured data, such as for business analytics, reporting, or data lake queries. Here's our take.

Microsoft Azure Synapse

Nice Pick

Developers should use Azure Synapse when building enterprise-scale data analytics solutions that require seamless integration between data warehousing and big data processing

Pros

• It is ideal for scenarios like real-time analytics, data lake exploration, and machine learning workflows, particularly in organizations already invested in the Microsoft Azure ecosystem
• Related to: azure-data-factory, apache-spark

Cons

• Specific tradeoffs depend on your use case

Amazon Redshift

Developers should learn and use Amazon Redshift when building data warehousing solutions that require fast query performance on large volumes of structured and semi-structured data, such as for business analytics, reporting, or data lake queries

Pros

• It is particularly valuable in cloud-native environments where scalability, cost-efficiency, and integration with AWS ecosystems (like S3, Glue, and QuickSight) are priorities, making it ideal for enterprises handling big data or migrating from on-premises data warehouses
• Related to: aws, sql

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Microsoft Azure Synapse is a platform while Amazon Redshift is a database. We picked Microsoft Azure Synapse based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Microsoft Azure Synapse wins

Based on overall popularity. Microsoft Azure Synapse is more widely used, but Amazon Redshift excels in its own space.