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Difference between OLAP and OLTP in DBMS

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Pre-Requisite: OLAP, OLTP

OLAP stands for Online Analytical Processing. OLAP systems have the capability to analyze database information of multiple systems at the current time. The primary goal of OLAP Service is data analysis and not data processing. 

OLTP stands for Online Transaction Processing. OLTP has the work to administer day-to-day transactions in any organization. The main goal of OLTP is data processing not data analysis.

Online Analytical Processing (OLAP)

Online Analytical Processing (OLAP) consists of a type of software tool that is used for data analysis for business decisions. OLAP provides an environment to get insights from the database retrieved from multiple database systems at one time. 

OLAP Examples

Any type of Data Warehouse System is an OLAP system. The uses of the OLAP System are described below.

  • Spotify analyzed songs by users to come up with a personalized homepage of their songs and playlist.
  • Netflix movie recommendation system.


Benefits of OLAP Services

  • OLAP services help in keeping consistency and calculation.
  • We can store planning, analysis, and budgeting for business analytics within one platform.
  • OLAP services help in handling large volumes of data, which helps in enterprise-level business applications.
  • OLAP services help in applying security restrictions for data protection.
  • OLAP services provide a multidimensional view of data, which helps in applying operations on data in various ways.

Drawbacks of OLAP Services

  • OLAP Services requires professionals to handle the data because of its complex modeling procedure.
  • OLAP services are expensive to implement and maintain in cases when datasets are large.
  • We can perform an analysis of data only after extraction and transformation of data in the case of OLAP which delays the system.
  • OLAP services are not efficient for decision-making, as it is updated on a periodic basis.

Online Transaction Processing (OLTP)

Online transaction processing provides transaction-oriented applications in a 3-tier architecture. OLTP administers the day-to-day transactions of an organization. 

OLTP Examples

An example considered for OLTP System is ATM Center a person who authenticates first will receive the amount first and the condition is that the amount to be withdrawn must be present in the ATM. The uses of the OLTP System are described below.

  • ATM center is an OLTP application.
  • OLTP handles the ACID properties during data transactions via the application.
  • It’s also used for Online banking, Online airline ticket booking, sending a text message, add a book to the shopping cart.


Benefits of OLTP Services

  • OLTP services allow users to read, write and delete data operations quickly.
  • OLTP services help in increasing users and transactions which helps in real-time access to data.
  • OLTP services help to provide better security by applying multiple security features.
  • OLTP services help in making better decision making by providing accurate data or current data.
  • OLTP Services provide Data Integrity, Consistency, and High Availability to the data.

Drawbacks of OLTP Services

  • OLTP has limited analysis capability as they are not capable of intending complex analysis or reporting.
  • OLTP has high maintenance costs because of frequent maintenance, backups, and recovery.
  • OLTP Services get hampered in the case whenever there is a hardware failure which leads to the failure of online transactions.
  • OLTP Services many times experience issues such as duplicate or inconsistent data.

Difference between OLAP and OLTP

Category OLAP (Online Analytical Processing) OLTP (Online Transaction Processing)
Definition It is well-known as an online database query management system. It is well-known as an online database modifying system.
Data source Consists of historical data from various Databases. Consists of only operational current data. 
Method used It makes use of a data warehouse. It makes use of a standard database management system (DBMS).
Application It is subject-oriented. Used for Data Mining, Analytics, Decisions making, etc. It is application-oriented. Used for business tasks.
Normalized In an OLAP database, tables are not normalized. In an OLTP database, tables are normalized (3NF).
Usage of data The data is used in planning, problem-solving, and decision-making. The data is used to perform day-to-day fundamental operations.
Task It provides a multi-dimensional view of different business tasks. It reveals a snapshot of present business tasks.
Purpose It serves the purpose to extract information for analysis and decision-making. It serves the purpose to Insert, Update, and Delete information from the database.
Volume of data A large amount of data is stored typically in TB, PB The size of the data is relatively small as the historical data is archived in MB, and GB.
Queries Relatively slow as the amount of data involved is large. Queries may take hours. Very Fast as the queries operate on 5% of the data.
Update  The OLAP database is not often updated. As a result, data integrity is unaffected. The data integrity constraint must be maintained in an OLTP database.
Backup and Recovery It only needs backup from time to time as compared to OLTP. The backup and recovery process is maintained rigorously
Processing time The processing of complex queries can take a lengthy time. It is comparatively fast in processing because of simple and straightforward queries.
Types of users This data is generally managed by CEO, MD, and GM. This data is managed by clerksForex and managers.
Operations Only read and rarely write operations. Both read and write operations.
Updates With lengthy, scheduled batch operations, data is refreshed on a regular basis. The user initiates data updates, which are brief and quick.
Nature of audience The process is focused on the customer.    The process is focused on the market. 
Database Design Design with a focus on the subject.  Design that is focused on the application.
Productivity Improves the efficiency of business analysts. Enhances the user’s productivity.

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Last Updated : 01 May, 2023
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