What is HTAP?
The popularity of large-scale real-time analytics applications (real-time inventory/pricing, recommendations from mobile apps, fraud detection, risk analysis, IoT, etc.) keeps rising. These applications require distributed data management systems that can handle fast concurrent transactions (OLTP) and analytics on the recent data. Some of them even need running analytical queries (OLAP) as part of transactions. Efficient processing of individual transactional and analytical requests, however, leads to different optimizations and architectural decisions while building a data management system. For the kind of data processing that requires both analytics and transactions, Gartner recently coined the term Hybrid Transactional/Analytical Processing (HTAP). Many HTAP solutions are emerging both from the industry as well as academia that target these new applications. However, there is no standard set of capabilities all of these systems support. The goal of this project is to understand the HTAP landscape and develop a benchmark suite that would be representative of the different set of use cases that fall under the HTAP umbrella.