What is the difference between OLTP and OLAP

Today's data processing can be roughly divided into two categories: online transaction processing OLTP (on-line transaction processing), online analytical processing OLAP (On-Line Analytical Processing). OLTP is the main application of traditional relational databases, mainly for basic, daily transaction processing, such as bank transactions. OLAP is the main application of data warehouse systems, supporting complex analytical operations, focusing on decision support, and providing intuitive and easy-to-understand query results.
OLTP:
Also known as transaction-oriented processing systems, its basic feature is that customers' original data can be transmitted immediately Go to the computing center for processing, and give the processing results in a very short time.
The biggest advantage of doing this is that the incoming data can be processed in real time, and answers can be answered in a timely manner. Also known as real-time system (Real time System). An important performance indicator to measure the online transaction processing system is the system performance, which is embodied in the real-time response time (Response Time), that is, the time it takes for the computer to reply to the request after the user enters the data on the terminal. OLTP is done by the database engine.
OLTP databases are designed to allow transactional applications to write only the data they need to process a single transaction as quickly as possible.
OLAP:
Abbreviated as OLAP, with the development and application of database technology, the amount of data stored in databases has transitioned from mega (M) bytes and giga (G) bytes in the 1980s to terabytes (T) words now. At the same time, the query requirements of users are becoming more and more complex, which involves not only querying or manipulating one or several records in a relational table, but also querying millions of records in multiple tables. Data analysis and information synthesis are carried out on the data of each record, and the relational database system can no longer meet this requirement. In foreign countries, many software manufacturers have adopted the development of their front-end products to make up for the lack of support of relational database management systems, trying to unify the scattered public application logic, and respond to the complex query requirements of non-data processing professionals in a short time.
Online Analytical Processing (OLAP) system is the most important application of data warehouse system. It is specially designed to support complex analysis operations, focusing on decision support for decision makers and senior managers. Complex query processing of data volume, and provide query results to decision makers in an intuitive and easy-to-understand form, so that they can accurately grasp the business status of enterprises (company), understand the needs of objects, and formulate correct solutions.