Amazon Athena vs Azure Synapse Serverless SQL vs Google BigQuery
Serverless SQL query services enable users to run ad-hoc SQL queries directly on cloud storage — no need to provision or manage infrastructure. These services are increasingly popular for data lake analytics, BI, and quick insights:
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Amazon Athena
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Azure Synapse Serverless SQL Pools
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Google BigQuery
This article provides an expert Level 500 comparison of architecture, capabilities, performance, use cases, and pricing.
Core Capabilities
| Feature | Amazon Athena | Azure Synapse Serverless SQL Pools | Google BigQuery |
|---|---|---|---|
| Primary Use Case | Serverless SQL on S3 data lakes | Serverless SQL on Azure Data Lake | Serverless data warehouse & SQL on Cloud Storage |
| Deployment Model | Fully serverless | Fully serverless | Fully serverless |
| Storage Integration | Amazon S3 | Azure Data Lake Storage Gen2, Blob | Google Cloud Storage |
| Query Language | ANSI SQL + HiveQL | T-SQL | Standard SQL |
| Result Storage | S3 | Azure Storage | BigQuery tables or external |
Architecture & Scalability
| Feature | Amazon Athena | Azure Synapse Serverless SQL Pools | Google BigQuery |
|---|---|---|---|
| Serverless Compute Scaling | Automatic scaling | Automatic scaling | Automatic scaling |
| Concurrency | High | High | Very High |
| Multi-region Support | Yes | Limited | Yes (global service) |
| Storage-Compute Separation | Yes | Yes | Yes |
Advanced Capabilities
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Amazon Athena:
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Query Parquet, ORC, JSON, CSV, and more.
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Integrated with AWS Glue Data Catalog.
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Federated queries across relational DBs and other AWS services.
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Pay per query (per TB scanned).
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Azure Synapse Serverless SQL Pools:
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Query CSV, Parquet, JSON in Azure Data Lake.
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T-SQL language support.
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Tight integration with Power BI and Synapse Pipelines.
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Pay per query (per TB processed).
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Google BigQuery:
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Native columnar storage + external tables.
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Supports federated queries across GCS, Bigtable, and Spanner.
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Integrated ML (BigQuery ML).
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Advanced BI Engine acceleration.
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Pay per query (per TB processed) or flat-rate pricing.
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Real-world Scenario: Ad-hoc Analytics on Data Lake
A media company wants to run ad-hoc BI queries and interactive dashboards on petabytes of video and streaming data:
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Amazon Athena: Interactive SQL over Parquet data stored in S3, dashboards via Amazon QuickSight.
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Azure Synapse Serverless SQL: T-SQL queries over Azure Data Lake Gen2, connected to Power BI for reporting.
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Google BigQuery: Unified SQL access to Cloud Storage, BigQuery native storage, and Bigtable — with Looker for BI.
Performance Metrics
| Metric | Amazon Athena | Azure Synapse Serverless SQL Pools | Google BigQuery |
|---|---|---|---|
| Query Startup Time | ~5-10 sec | ~3-5 sec | ~2-3 sec |
| Query Throughput | High | High | Very High |
| Partition Pruning | Yes | Yes | Yes |
| Data Format Optimization | Parquet/ORC preferred | Parquet/ORC preferred | Columnar native format |
Costing Models
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Amazon Athena:
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$5 per TB scanned (pricing may vary by region).
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Additional costs for Glue Data Catalog.
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Azure Synapse Serverless SQL Pools:
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$5 per TB processed (pricing may vary).
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No cluster management fees.
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Google BigQuery:
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$5 per TB processed.
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Option for flat-rate pricing for predictable workloads.
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Advanced slot-based model for enterprise.
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Disclaimer
This article is independently developed and not affiliated with or endorsed by Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP). All service names, prices, and descriptions are based on publicly available sources as of June 2025 and may change.
