OLTP concept
OLTP (OnLine Transacion Processing) online transaction processing is the main application of traditional relational database, primarily for basic, routine transactions, such as bank transactions. It is a processing system for transaction, characterized in that substantially immediately transmitting and processing the raw data, i.e., real-time process data and gives a response, which is also called real-time response systems .
Our daily development, is used in more types of OLTP database, and we usually say sql execution time, that can be understood as OLTP response times. Therefore, a measure OLTP performance is an important indicator is the real-time response time, that get results obtained from the user input to the time.
The basic characteristics of OLTP:
1, real-time requirements of high
2, the amount of data the query is not particularly large
3, transactions are generally determined, it is the certainty of data access
4, high concurrency requirements, and strict requirements affairs integrity, security
5, when a large number of short transactional operations, but also for OLTP type of database
OLAP concept
OLAP (OnLine Analysis Processing) online analytical processing, analysis with flexible, intuitive data manipulation and visual representation of the analysis results and other advantages, so that the user easy and efficient analysis of large complex data based. His focus is on the analysis of large amounts of data, real-time without stress.
OLAP is characterized by relatively low trading volume. Queries are usually very complex and involves aggregation. OLAP applications are widely used data mining techniques. There in the OLAP database of historical data aggregated, stored in a multidimensional model (usually a star schema) in. Sometimes query needs to access large amounts of data management records, statistics such as annual income, water and other data.
The basic characteristics of OLAP:
1, real-time requirements are not very high. As you can imagine, a lot of statistical data are regularly to statistics
2, data volume. Statistics, the amount must be relatively large
3, complex queries, and it is clear and easy to see
4, because the focus on analysis and decision support, it is dynamic queries
Application examples
For example, there is a tram's Web site, you need to provide user registration, user login, the user modifies the basic functions of information, purchase, etc., similar modifications, purchase and other operations, are some small transactions. This time, OLTP is clearly more suitable.
As the owner of the electricity supplier site, you may be more concerned about the purchase of the site or earnings data analysis of each commodity , or for more advanced electricity supplier site, but also for the information of the user purchases or age, make personalized recommendations. The scene is clearly more suitable for OLAP.