Azure Data Explorer vs Google BigQuery

Developers should learn Azure Data Explorer when working with large-scale, real-time data analytics, especially for use cases like application monitoring, IoT device telemetry, and security log analysis 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 Data Explorer

Nice Pick

Developers should learn Azure Data Explorer when working with large-scale, real-time data analytics, especially for use cases like application monitoring, IoT device telemetry, and security log analysis

Pros

• It is ideal for scenarios requiring rapid ingestion and querying of streaming data, such as operational intelligence, where traditional databases may struggle with performance
• Related to: kusto-query-language, azure-monitor

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 Data Explorer is a platform while Google BigQuery is a database. We picked Azure Data Explorer based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Azure Data Explorer wins

Based on overall popularity. Azure Data Explorer is more widely used, but Google BigQuery excels in its own space.