Azure Synapse Analytics

SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.
Import big data into SQL Data Warehouse with simple PolyBase T-SQL queries, and then use the power of MPP to run high-performance analytics.
SQL Data Warehouse stores data into relational tables with columnar storage.
This format significantly reduces the data storage costs, and improves query performance.
Compared to traditional database systems, analysis queries finish in seconds instead of minutes, or hours instead of days.
To save costs, you can pause and resume compute resources on-demand.
- For example, if you won't be using the database during the night and on weekends, you can pause it during those times, and resume it during the day.
- You won't be charged for compute resources while the database is paused. However, you will continue to be charged for storage.
You can increase or decrease compute resources by adjusting data warehouse units.
SQL Data Warehouse uses a node-based architecture.
- Applications connect and issue T-SQL commands to a Control node, which is the single point of entry for the data warehouse.
- The Control node runs the MPP engine which optimizes queries for parallel processing, and then passes operations to Compute nodes to do their work in parallel.
- The Compute nodes store all user data in Azure Storage and run the parallel queries.
- The Data Movement Service (DMS) is a system-level internal service that moves data across the nodes as necessary to run queries in parallel and return accurate results.
With decoupled storage and compute, SQL Data Warehouse can:
- Independently size compute power irrespective of your storage needs.
- Grow or shrink compute power without moving data.
- Pause compute capacity while leaving data intact, so you only pay for storage.
- Resume compute capacity during operational hours.