Difference Between OLTP and OLAP

DBMSDatabaseBig Data Analytics

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


  • 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.


  • 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.

Updated on 25-Mar-2021 06:16:56