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Difference between Oracle and dBASE
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Difference Between OLAP and OLTP in Databases

Last Updated : 28 Jan, 2025
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OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) are both integral parts of data management, but they have different functionalities.

  • OLTP focuses on handling large numbers of transactional operations in real time, ensuring data consistency and reliability for daily business operations.
  • OLAP is designed for complex queries and data analysis, enabling businesses to derive insights from vast datasets through multidimensional analysis.

Online Analytical Processing (OLAP)

Online Analytical Processing (OLAP) refers to software tools used for the analysis of data in business decision-making processes. OLAP systems generally allow users to extract and view data from various perspectives, many times they do this in a multidimensional format which is necessary for understanding complex interrelations in the data. These systems are part of data warehousing and business intelligence, enabling users to do things like trend analysis, financial forecasting, and any other form of in-depth data analysis.

OLAP Examples

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

  • Spotify personalizes homepages with custom songs and playlists based on user preferences.
  • Netflix movie recommendation system.
Difference-between-OLAP-and-OLTP-in-DBMS-1

Benefits of OLAP Services

  • Helps in keeping consistency and performing calculation on data.
  • Can store planning, analysis, and budgeting for business analytics within one platform.
  • Efficiently handle large volumes of data, making them suitable for enterprise-level business applications.
  • Assist in applying security restrictions for data protection.
  • Provide a multidimensional view of data, which helps in applying operations on data in various ways.

Drawbacks of OLAP Services

  • Requires professionals to handle the data because of its complex modeling procedure.
  • Expensive to implement and maintain in cases when datasets are large.
  • Data analysis occurs only after extraction and transformation, leading to system delays.
  • Not efficient for decision-making, as it is updated on a periodic basis.

Online Transaction Processing (OLTP)

Online Transaction Processing, commonly known as OLTP, is a data processing approach emphasizing real-time execution of transactions. The majority of OLTP systems are meant to manage numerous short atomic operations that keep databases in line. To maintain transaction integrity and reliability, these systems support ACID (Atomicity, Consistency, Isolation, Durability) properties. It is through this that numerous unavoidable applications run their critical courses like online banking, reservation systems etc.

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.
Difference-between-OLAP-and-OLTP-in-DBMS-2

Benefits of OLTP Services

  • Allow users to quickly read, write, and delete data operations.
  • Support an increase in users and transactions for real-time data access.
  • Provide better data protection through multiple security features.
  • Aid in decision-making with accurate, up-to-date data.
  • Ensure data integrity, consistency, and high availability.

Drawbacks of OLTP Services

  • Limited analysis capability, not suited for complex analysis or reporting.
  • High maintenance costs due to frequent updates, backups, and recovery.
  • Susceptible to disruption during hardware failures, impacting online transactions.
  • Prone to issues like 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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Difference between Oracle and dBASE

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