Definition of OLTP
Online Transactional Processing, or OLTP, is a class of software program capable of supporting transaction-oriented applications on the internet.
In computing, a transaction is a sequence of discrete information or data. Many everyday applications involve OLTP, from online banking, shopping, and POS terminals.
The advantages of OLTP are its ability to handle many transaction requests simultaneously (called concurrency) and the ability to reliably backup and continue if part of the system fails (called atomicity).
It allows its users to perform operations like read, write and delete data quickly. It responds to its user actions immediately as it can process queries very quickly.
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How do I Use OLTP?
OLTP typically involves inserting, updating or deleting small amounts of data into a database. ATMs are the typical example of OLTP technology.
The databases handled by OLTP become the sources of data for Online Analytical Processing (OLAP), online analysis and data retrieving process that entered the BI space over 20 years ago.
What value does it provide?
Because OLTP systems often serve a large number of users and access often deal with mission-critical data (like an online shopping cart), they typically require extremely high availability and security protocols.
- Speedy response times
- Indexed access to data
- Frequent updates and queries
- Transactions involving small amounts of data
- Many users
OLAP applications display these characteristics:
- Lower volume of transactions.
- Complex and involved queries across aggregated data sets
- Multi-dimensional views of various kinds of business activities that help users with problem-solving, planning, and decision support
- Long-running batch jobs to refresh the data
Deep Dive: In-Memory OLTP
In-Memory OLTP is a database engine component that fully integrates into SQL Server’s Database Engine.
In-Memory OLTP encompasses features such as memory-optimized tables and table types, as well as a native compilation of Transact-SQL stored procedures for efficient access to these tables.
In-Memory OLTP may be used in the same manner as any other Database Engine component.
Key Risks of Using OLTP
While using OLTP to transfer data between live applications can be extremely useful, handling your data with OLTP databases creates two challenges:
- An overwhelming amount of raw data – Data teams need a way to turn all of that raw information into actionable knowledge and insights.
- Data silos – Silos are a natural result of the OLTP architecture, in which each application has its own database. OLTP databases simply aren’t built to allow analytics that span across each database silo.