Azure Synapse Analytics vs Google BigQuery

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 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.

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

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. Azure Synapse Analytics is a platform while Google BigQuery 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 Google BigQuery excels in its own space.