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Difference Between OLTP and OLAP
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.
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