OLTP (Online Transaction Processing), OLAP (Online Analytical Processing), and HTAP (Hybrid Transaction/Analytical Processing) are three commonly used database architectures that are designed to support different types of workloads.


OLTP is optimized for handling large numbers of small, short-lived transactions that update or retrieve data from a database. This type of architecture is commonly used in systems that require real-time data access, such as e-commerce or financial applications. OLTP databases are designed to be fast and efficient, and they often use indexing and other optimization techniques to speed up data access.


OLAP is designed to support analytical workloads, such as data mining, reporting, and business intelligence. OLAP systems typically use a multidimensional data model, which allows users to analyze data from multiple perspectives and at different levels of detail. OLAP systems are often used in decision support applications, where users need to quickly and easily analyze large amounts of data.


HTAP is a hybrid architecture that combines the capabilities of OLTP and OLAP systems. This allows HTAP databases to support both transactional and analytical workloads, providing real-time data access and analysis capabilities in a single system. HTAP systems are often used in applications that require both transactional and analytical processing, such as real-time recommendation engines or fraud detection systems.