Definition of OLTP, that stands for On Line Transactional Processing and database transactions. The abbreviation OLTP refers to all databases designed to manage data processing in a transactional and reliable manner. This is for general operational management purposes.
Examples include accounting data, supermarket sales data such as receipts and bank transactions.
Definition of transactional databases or OLTP: On Line Transactional Processing
First of all, the notion of a single and indivisible transaction is fundamental in OLTP. For example, a sale is validated or cancelled in its entirety. This is data that is updated transaction by transaction, in a “transactional” way. This is in contrast to batch processing or multidimensional databases.
What kind of data processing do transactional or OLTP databases use?
To go further, online transaction processing, or OLTP, refers to a class of systems that facilitate and manage transactional applications. Typically for the capture and processing of retrieval transactions.
Furthermore, the term is somewhat ambiguous, some see it as a transaction within the context of computer or database operations. While others (such as the Transaction Processing Performance Council) define it as economic or commercial transactions. That is, transactions related to the commercial activity of an organisation.
Indeed, OLTP has also been used as processing in which the system responds immediately to user requests. An example of a business transaction processing application is an ATM for a bank.
Difference between an OLTP database and an OLAP cube
OLAP systems are designed to be used by data scientists, business analysts and functional analysts. They support business intelligence applications, such as business intelligence, data mining and other decision support applications.
OLTP systems, on the other hand, are optimised for processing massive numbers of transactions. They are designed to be used by employees in operational and sometimes critical areas.
OLTP and standard database transactions are designed for a robust single data operation handling.
Active data warehouses
Many data warehouses today are looking for an OLTP application. This is often referred to as an active data warehouse. This warehouse is completely different from traditional data warehousing. Because the processing is close to real time to provide up-to-date data to business users.
Finally, here is the presentation of the data warehouse with Ralph Kimball approach.
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