Microsoft Azure Synapse vs Google BigQuery

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 google bigquery when working with massive datasets that require fast, scalable analytics, such as in data warehousing, log analysis, or real-time reporting for applications. 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

Google BigQuery

Developers should learn and use Google BigQuery when working with massive datasets that require fast, scalable analytics, such as in data warehousing, log analysis, or real-time reporting for applications

Pros

• It is particularly valuable in cloud-native environments where serverless operations reduce overhead, and its integration with Google Cloud services makes it ideal for projects leveraging GCP for data processing and AI/ML workflows
• Related to: google-cloud-platform, sql

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Microsoft Azure Synapse is a platform while Google BigQuery 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 Google BigQuery excels in its own space.