Hello WeirdMan !
Thank you for posting on Microsoft Learn.
I am summarizing the differences between Dedicated SQL Pools and Serverless SQL Pools in Azure Synapse Analytics, including their performance characteristics, use cases, and best practices—summarized in a table format:
Aspect | Dedicated SQL Pool | Serverless SQL Pool |
---|---|---|
Provisioning | Requires explicit resource provisioning (DWUs) | On-demand, no provisioning needed |
Provisioning | Requires explicit resource provisioning (DWUs) | On-demand, no provisioning needed |
Billing | Billed per hour based on DWU, regardless of usage | Billed per TB of data processed |
Performance | High performance for large, complex workloads | Suitable for ad-hoc, lightweight, or infrequent queries |
Scalability | Manually scalable (DWU scaling or pause/resume) | Auto-scales behind the scenes |
Data Storage | Stores data in dedicated distributed tables (example CCI) | Queries external data (e.g., in Data Lake using OPENROWSET) |
Latency | Lower latency for repeated queries on large data volumes | Higher latency for large data scans or repeated queries |
Data Source | Data stored in dedicated SQL pool tables | External data in ADLS Gen2, Cosmos DB, etc. |
Use Cases | - Large ETL workloads- Complex joins/aggregations- High concurrency- Data warehousing | - Data exploration- Quick dashboards- ELT validation- Cost-efficient ad-hoc analytics |
Optimization Options | Distribution, partitioning, indexing, materialized views | Limited optimization; best practices include filtering early |
Concurrency | Higher concurrency with proper scaling | Limited by backend resources; good for smaller user base |
Security & Governance | Advanced RBAC, auditing, managed VNET | Supports RBAC; less granular control compared to dedicated |
https://learn.microsoft.com/en-us/azure/synapse-analytics/sql/best-practices-dedicated-sql-pool
https://learn.microsoft.com/en-us/azure/synapse-analytics/sql/best-practices-serverless-sql-pool