BigQuery vs Microsoft Azure Synapse

Developers should learn BigQuery when working with large-scale data analytics, data warehousing, or business intelligence applications, especially in cloud-native environments meets developers should use azure synapse when building enterprise-scale data analytics solutions that require seamless integration between data warehousing and big data processing. Here's our take.

BigQuery

Nice Pick

Developers should learn BigQuery when working with large-scale data analytics, data warehousing, or business intelligence applications, especially in cloud-native environments

Pros

• It is ideal for scenarios requiring petabyte-scale querying, real-time analytics, or integration with Google's ecosystem, such as marketing analytics, IoT data processing, or financial reporting
• Related to: google-cloud-platform, sql

Cons

• Specific tradeoffs depend on your use case

Microsoft Azure Synapse

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

The Verdict

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

The Bottom Line

BigQuery wins

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