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24 November 2022

OLTP Vs OLAP | Difference | Comparison

OLTP stands for Online transaction procession. All transactions"(read, write, update, and delete) in an OLTP database must be completed, Otherwise, the database will be inconsistent. OLTP is often utilized when data must be kept up to date. OLAP stands for online analytical processing, It is a technology for analyzing data stored in a database. It is a method for storing and analyzing enormous amounts of data in a database. OLAP databases are used in multidimensional databases to store data. A multidimensional database stores data in a sequence of tables, each of which represents a dimension. 

What is OLTP?

OLTP stands for online transactional processing. It allows huge numbers of individuals to execute enormous numbers of database transactions in real time, generally over the internet. Many of our everyday transactions, from ATMs to in-store sales to hotel reservations are powered by OLTP systems. The non-financial transactions, such as password changes and text messages. 

What is OLAP?

OLAP stands for Online Analytical Processing. The OLAP database stores past data entered by OLTP. It enables the users to view several summaries of multidimensional data. With OLAP, you may extract data from a sizable database and analyze it to aid in decision-making.

OLTP Vs OLAP | Difference between OLTP and OLAP:

  • OLTP is an online transactional system. It manages database modification. Online analysis and data retrieval is known as OLAP.
  •  OLAP is characterized by a large number of short online transactions. While OLAP is characterized by a large volume of data.
  • OLTP uses traditional DBMS. OLAP uses the data warehouse.
  • OLTP is an online database modifying system. An online database query management system is known as OLAP.
  • Tables in the OLTP database are normalized. The OLAP database's tables are not normalized.
  • Insert data into the database, update it, then remove it with OLTP. While OLAP mostly selects operations.
  • OLTP and its transaction are the sources of data. Data for OLAP is sourced from various OLTP databases.
  • OLTP database must maintain data integrity constraints. OLAP database does not get frequently modified. Hence data integrity is not an issue.
  • OLTP response time is in milliseconds. While in OLAP response time is in seconds to minutes.
  • OLTP is a market-oriented process. While OLAP is a customer-oriented process.
  • OLTP allow read/write operations. While OLAP is only read and rarely written.
  • OLTP helps to control and run fundamental business tasks. While OLAP helps with planning, problem-solving, and decision support.
  • The data in the OLTP database is always detailed and organized. The data in the OLAP process might not be organized. 
  • OLTP, Queries in this process are standardized and simple. OLAP is a complex query involving aggregations.
  • OLTP backup of the data combined with incremental backups. Only occasionally does OLAP require a backup. OLTP is more crucial than backup.
  • OLTP is easy to create and maintain. OLAP lets the user create a view with the help of a spreadsheet.
  • OLTP is designed for real-time business operations. OLAP is designed for the analysis of business measures by category and attributes.
  • OLTP provides fast results for daily used data. OLAP ensures that the response to the query is quicker consistently.
  • OLTP is designed to have a fast response time and low data redundancy and is normalized. OLAP is a data warehouse created uniquely so that it can integrate different data sources for building a consolidated database. 
  • OLTP is used by data critical users like clerks, DBA, and database professionals. Users of data knowledge including employees, supervisors, and the CEO utilize OLAP.
  • OLTP transaction throughput is the performance metric. OLAP query throughput is the performance metric.
  • In OLTP, database users allow thousands of users. While the OLAP database allows only hundreds of users.
  • OLTP helps to increase users' self-service and productivity. OLAP help to increase the productivity of business analysts.
  • OLTP, data warehouses historically have been a development project which may prove costly to build. An open SQL server data warehouse is not the same as an OLAP cube. Therefore, operating the OLAP server requires both technical expertise and understanding.
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