Difference Between OLTP and OLAP

In this post, we will understand the difference between OLTP and OLAP.

OLTP

• It is an online transactional system.

• It is used to manage database modification.

• It has large number of short online transactions.

• It uses traditional DBMS.

• It performs operations such as ‘Insert’, ‘Update’, and ‘Delete’ operation.

• The OLTP tables are normalized.

• The system and its transactions are data sources.

• It has to maintain data integrity constraint.

• Its response time is in terms of milliseconds.

• The data in the OLTP database is detailed and organized all the time.

• It helps control and run the fundamental business tasks.

• It allows the read and write operations.

• It is considered a market orientated process.

• The queries here are standardized and simple.

• The backup of the data is always present, with incremental backups.

• The database designed is application oriented.

• It is used by data critical users such as DBA and database professionals.

• It has been designed to work efficiently with real time business operations.

• The performance metric is transaction throughput.

• It allows thousands of users.

• It helps increase user’s self-service and productivity.

• It is easy to create.

• It is easy to maintain.

• It provides quick results for daily usage data.

• It has been designed to have quick response time.

• It has low redundancy.

OLAP

• It is an online analysis and data retrieving process.

• It processes large volumes of data.

• It uses data warehouse.

• It performs ‘SELECT’ operations mostly.

• Multiple OLTP databases are data sources for OLAP.

• It isn’t modified frequently.

• Data integrity is maintained.

• The response time is in terms of seconds to minutes.

• The data in this process may not remain organized always.

• It is usually read operation, and write operation is rare.

• It helps with planning, in problem solving, and with decision support.

• It is considered a customer orientated process.

• It executes complex queries that involve aggregations.

• OLAP needs a backup of data from time to time.

• Backup operation is not vital.

• It is subject-oriented.

• It is used by data knowledge users such as managers, CEO.

• It has been designed to analyse the business measures by category and attributes.

• The performance metric is the query throughput.

• It allows hundreds of users only.

• It helps increase the productivity of business analysts.

• This cube is not an open SQL server data warehouse.

• It ensures that response time to the query is quick and consistent.

• It allows user to create a view using a spreadsheet.