OLTP vs. OLAP: What’s the Difference? (Plus Benefits and Examples)

OLTP and OLAP: The two terms look similar but refer to different kinds of systems. Online transaction processing (OLTP) captures, stores, and processes data from transactions in real time. Online analytical processing (OLAP) uses complex queries to analyze aggregated historical data from OLTP systems.

Online Analytical Processing (OLAP) is the term for a class of software tools used for data analysis in support of business decisions. OLAP offers a setting where users can simultaneously access insights from a number of different database systems. Examples: An OLAP system is any type of data warehouse system. The uses of OLAP are as follows:

OLAP vs OLTP | Online Transaction Processing vs Online Analytical Processing | Intellipaat

What is OLAP?

OLAP is a service for performing multidimensional analysis on large amounts of data. A dimension in this context refers to a component of a specific data set. For example, if a company has information about its advertising campaigns, including information about consumer exposure, the length of the ads, sales of the products, and the cost of the advertising, it can use OLAP to sort and analyze the information according to each component. Financial analysis, budgeting, forecasting, data mining, and complex analytical calculations are all common uses of OLAP in business.

What is OLTP?

An online database that automatically updates as transactions take place is used in OLTP, a technique for carrying out transactions in real-time. OLTP is frequently used by companies like banks, hotels, and restaurants to enable their staff and customers to carry out multiple transactions simultaneously and effectively while maintaining data accuracy. OLTP systems automatically update account balances and store other pertinent data like the date and time as transactions take place.

Benefits of OLTP systems

Benefits that companies may experience by using OLTP systems include:

Transactional automation

Employees completed transactions and kept financial records by hand or with simple computer systems before the advent of OLTP systems. OLTP automates this procedure to do away with the requirement for transactional data to be manually recorded. This can improve productivity, prevent revenue loss, and protect the integrity of business dealings.


Organizations can gain from the ability of OLTP algorithms to process multiple instances of transactional data concurrently while tracking the order of each transaction. One of these systems might be used by a hotel chain, for example, to track the availability of hotel rooms and ensure that it only offers rooms that are still available for sale. The system immediately reduces the number of available rooms in accordance with each transaction. The system automatically prevents customers from making a purchase once there are no more rooms available.


OLTP backups ensure the consistent reporting of transactional data. This might make it possible for customers and businesses to conduct dependable and uninterrupted transactions. Numerous advantages result from this dependability, including the ability to draw in repeat customers and guarantee data accuracy.

OLTP versus OLAP systems

Here are several major differences between OLTP and OLAP:

1. Uses

Businesses use OLTP for transactional purposes. The data inputs in OLTP come from value exchanges like customer purchases at a store. These systems process data simultaneously from various sources, tracking events down to the millisecond. This enables businesses to keep up-to-date records and guarantee the effectiveness of business transactions.

The uses for OLAP are more analytical. Data inputs come from various data sets, frequently containing a number of variables or components, like annual financial data or sales figures. Data analysts use OLAP services to aid in the completion of queries, which are simultaneous requests for particular types of information from numerous data sets. These services can help organize data to find trends, laws, and patterns that can help businesses accomplish specific objectives, like increasing sales revenue.

2. Processing speeds

To ensure that transactional information is updated, OLTP processes data quickly. For instance, if you have $500 in your bank account and you spend $490 on something, your account may track the transaction right away and show your new balance as $10. This effectiveness may be the result of your bank connecting your account to an OLTP system to prevent account overdrafts.

OLAP systems process data quickly, but they might not deliver results right away. There is frequently no need for the ongoing tracking and updates that OLTP features provide because the inputs for these systems don’t come from the same sources at the same time.

3. Required expertise

OLTP systems are used by a variety of workers, including entry-level workers, in a number of different industries. For instance, if a cash register’s automatic connection to a point-of-service system (POS), which carries out online transaction processing for many physical businesses through a software interface, allows cash register operators to use OLTP systems. OLTP systems are typically simple to use by employees of any level of expertise.

Users of OLAP services typically have some experience with data analysis. It might be necessary to have some familiarity with the system or the analytical techniques being used in order to enter specific queries and interpret their results. As an illustration, a specific system might call for users to interpret statistical information like proportions, means, or standard scores.

4. Backup frequency

In OLTP systems, data backups happen frequently to guarantee that data is consistently reliable and accessible. To guarantee data is preserved, these systems may employ a backup server or a collection of numerous servers. Due to the significance and sensitivity of financial transactions, businesses and consumers frequently rely on OLTP systems to operate correctly and effectively. In contrast, OLAP systems only occasionally perform backups to guarantee that all data is safe and accessible.

5. Complexity of queries

Because they only deal with additions and subtractions of transactional amounts, OLTP queries are frequently straightforward. OLAP queries typically involve the analysis of multiple variables from multidimensional data sets and are more complicated. For instance, to find the products that generated the most revenue based on each day of the week, you could enter a query into an OLAP system that contains the financial data from the previous year. Data can be sorted by day, product type, and overall revenue in the system, giving analysts important information about the query.

6. Data normalization

OLAP systems don’t normalize their data because each input is equally significant. Data normalization frequently takes place in OLTP systems to account for anomalies, data duplication, and outliers. This normalization helps facilitate the accurate analysis of data sets.

Benefits of OLAP systems

Here are a few advantages that businesses might gain from utilizing OLAP systems:

Data mining

Data mining is a technique used by analysts to find anomalies, patterns, and correlations in massive data sets and forecast outcomes. OLAP systems can be used to summarize data and assist experts in performing in-depth analyses. For instance, an OLAP system can speed up data processing and analysis when a data set contains millions of data points.

Trend analysis

Once you mine data, its available for trend analysis. Trend analysis is frequently performed using the cube method in OLAP systems, which entails sorting data into various dimensions according to variables, building layers of stacked tables, and creating the appearance of a cube. These systems can then group the data into different cubes according to the criteria of a specific query, making trend analysis simpler.

Computational automation

Once you enter a query into an OLAP system, it may also automatically process computations of enormous data structures. By doing so, analysts’ manual computation efforts can be reduced, increasing their efficiency and accuracy. To help accountants produce accurate balance sheets, analysts might be able to add transaction values and expenses, for instance.

OLTP system examples

Here are examples of OLTP system use:

Airline company example

An airline company called FastSkies uses OLTP systems to take reservations for its flights. The system automatically removes those seats from the flight’s inventory as customers purchase tickets and select seats, processing the transaction. FastSkies has a policy to never overbook a flight, making certain that everyone who purchases a seat does so on the desired day of the flight. FastSkies is able to uphold this policy thanks to the OLTP system, and as a result, the business attracts a significant number of devoted clients who value its swift and accurate services.

Credit union example

FamilyRun Credit Union tracks every transaction made by a customer using OLTP. Customers can access their FamilyRun accounts to view the most recent transaction data and send money to other FamilyRun users right away. OLTP makes sure that transactions are recorded on the account as soon as they happen and that the balances are accurate at all times.

OLAP system examples

Here are examples of OLAP system use:

Retail chain example

PartyHearty, a national retailer, is studying data from its most recent advertising campaign. The company’s marketing staff has information about the target market’s location, advertising style, revenue generation, and type of product. They enter the data into their OLAP service, which provides them with organized and simple-to-understand data sets, in order to categorize, identify trends, and forecast outcomes for their next campaign. They use these data sets to pinpoint areas where future campaigns can be improved.

Finance company example

A financial startup company’s professionals use an OLAP service to examine their annual sales data. To more accurately determine their sales strategies for the following year, they insert data pertaining to sales revenue, customer descriptions, profit margins, overhead costs, sales associates, and location. They come to the conclusion that a few salespeople excel when they are selling a specific product in a particular area. The startup establishes a presence there and elevates the sales representatives to sales managers, both of which increase profit margins.

Tips for choosing OLTP versus OLAP

While some businesses only use one of these data processing systems, many businesses choose to use both OLTP and OLAP. Examine the following advice to see if utilizing these systems is best for you:


Is data warehouse OLAP or OLTP?

Data Warehouse is the example of OLAP system. OLTP stands for On-Line Transactional processing. It is used to maintain the integrity of records and online transactions in environments with multiple users. A system known as OLTP is used to manage a sizable number of quick online transactions, such as ATM transactions.

What is OLTP example?

A typical data processing system in modern businesses is an OLTP system. Order entry, retail sales, and financial transaction systems are traditional examples of OLTP systems.

What are the advantages of OLAP over OLTP?

A typical data processing system in modern businesses is an OLTP system. Order entry, retail sales, and financial transaction systems are traditional examples of OLTP systems.

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