Azure Synapse Analytics vs Amazon Redshift

Developers should use Azure Synapse Analytics when building large-scale data analytics solutions that require processing and analyzing massive datasets from diverse sources 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.

Azure Synapse Analytics

Nice Pick

Developers should use Azure Synapse Analytics when building large-scale data analytics solutions that require processing and analyzing massive datasets from diverse sources

Pros

• It is ideal for scenarios like real-time analytics, business intelligence reporting, and machine learning workflows, as it reduces the complexity of managing separate data services
• 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. Azure Synapse Analytics is a platform while Amazon Redshift is a database. We picked Azure Synapse Analytics based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Azure Synapse Analytics wins

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