Azure Synapse Serverless SQL Architecture¶
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Overview¶
Azure Synapse Serverless SQL is a serverless query engine that enables you to query data in your data lake using SQL without managing any infrastructure. It works seamlessly with Delta Lakehouse and provides several advantages over traditional SQL databases.
Key Features¶
1. Serverless Architecture¶
- No infrastructure management
- Pay-per-query pricing
- Automatic scaling
- High availability
2. Data Access¶
- Query data directly from ADLS Gen2
- Support for multiple file formats:
- Parquet
- Delta
- CSV
- JSON
- Avro
3. Performance Optimizations¶
- Pushdown predicates
- Columnar processing
- Caching
- Query optimization
Architecture Components¶
1. External Tables¶
- Define schema over existing data
- Support for partitioned data
- Statistics collection
- Row-level security
2. Views¶
- Materialized views
- Regular views
- Security views
3. Security¶
- Role-based access control
- Row-level security
- Column-level security
- Secure data access
Shared Metadata Architecture¶

Best Practices¶
Schema Design¶
- Use appropriate data types
- Implement proper statistics
- Use meaningful column names
- Plan for schema evolution
Performance¶
- Use appropriate partitioning
- Implement proper indexing
- Use query hints when needed
- Regularly update statistics
Security¶
- Implement proper RBAC
- Use row-level security
- Regularly audit access
- Use secure connection strings
Code Examples¶
Creating External Tables¶
CREATE EXTERNAL TABLE my_table
WITH (
LOCATION = 'abfss://container@storageaccount.dfs.core.windows.net/path',
DATA_SOURCE = my_datasource,
FILE_FORMAT = parquet_format
)
AS SELECT * FROM source_table
Creating Views¶
Query Optimization¶
SELECT /*+ PUSHDOWN */
customer_id,
COUNT(*) as order_count
FROM orders
WHERE order_date >= '2024-01-01'
GROUP BY customer_id
Next Steps¶
- Shared Metadata Architecture
- Best Practices
- Code Examples
- Security Guide