Introduction
Hybrid Transactional / Analytical Processing (HTAP) is a style of data processing that combines transactional data processing, such as is typically found in a business application, with analytical processing, such as is used in a business intelligence (BI) or reporting solution. The data access patterns and storage optimizations used in these two kinds of workload are very different, so usually a complex extract, transform, and load (ETL) process is required to copy data out of transactional systems and into analytical systems; adding complexity and latency to data analysis. In an HTAP solution, the transactional data is replicated automatically, with low-latency, to an analytical store, where it can be queried without impacting the performance of the transactional system.
In Azure Synapse Analytics, HTAP capabilities are provided by multiple Azure Synapse Link services, each connecting a commonly used transactional data store to your Azure Synapse Analytics workspace and making the data available for processing using Spark or SQL.
After completing this module, you'll be able to:
- Describe Hybrid Transactional / Analytical Processing patterns.
- Identify Azure Synapse Link services for HTAP.