Skip to content

Serverless SQL Architecture

🏠 Home > 🏗️ Architecture > 📄 Serverless SQL

Serverless SQL architecture in Azure Synapse Analytics allows you to query data directly in your data lake without moving or copying data, using familiar T-SQL syntax.

Documentation

  • Serverless SQL Overview - Introduction to Serverless SQL capabilities
  • Detailed Architecture - Comprehensive technical architecture of Serverless SQL implementation

Key Features

  • On-demand querying with no infrastructure to manage
  • Pay-per-query cost model
  • T-SQL compatibility
  • Native integration with Azure Data Lake Storage
  • Built-in data virtualization
  • Seamless integration with visualization tools

Architecture Overview

Serverless SQL Pool Architecture

Serverless SQL pools in Azure Synapse Analytics provide a serverless distributed query processing engine for big data analytics. The architecture is designed to support on-demand query execution over data stored in your data lake without the need to manage infrastructure.

Implementation Considerations

Data Organization

Organize your data lake with a clear folder structure to optimize query performance:

adls://data/
├── raw/
├── curated/
│   ├── dimensions/
│   └── facts/
└── external/

File Formats and Optimization

For best performance with Serverless SQL:

  • Use Parquet for columnar storage benefits
  • Partition large datasets appropriately
  • Create statistics on frequently queried columns
  • Use external tables with OPENROWSET for flexibility