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OLAP vs OLTP: Head-to-Head Comparison [2022]

Posted in database, OLTP, OLAP

As opposed to a batch processing system, where transaction details pile up in a stack of documents that are then registered in batches, an online processing system is one that registers ongoing transactions in real time. OLAP and OLTP are both such online processing systems. 

Here, we compare the differences between OLAP and OLTP, including their respective pros and cons. We also talk about what exactly OLAP and OLTP are. We start off with a quick summary of the differences.

OLTP vs OLAP: Head-to-Head Comparison

Parameters

OLAP

OLTP

Backup and Recovery

OLAP systems require backup less frequently

A complete backup at any moment in time is mandatory along with some kind of provision for incremental backups

Data

It makes use of the data warehouse concept and is an online database query management system

Relies on traditional database management systems

Data Integrity

OLAP systems go through infrequent transactions. Hence, OLAP systems don’t necessarily require data integrity

Data integrity can’t be ignored when OLTP systems are concerned as the OLTP system frequently executes transactions that modify the database

Primary Intent

Allows the user to retrieve/extract multidimensional data that can be analyzed and used for decision making.

Focuses on inserting, updating, and sometimes deleting information from the database

Storage Space Requirements

Asks for significant storage space due to the existence of aggregation structures and historical data

Requires smaller storage space and even smaller space for those systems with archived historical data

System Type

An online data retrieval and analysis system

An online transaction system

Transactions

Transactions are longer but less frequent

Short and fast, but the frequency of transactions is higher

Query Complexity

Complex queries

Simple queries

Audience

Customer-oriented

Market-oriented

Normalization

Tables are not normalized

Tables are normalized

Response time

In seconds to minutes

In milliseconds

What is OLAP (Online Analytical Processing)?

An Online Analytical Processing (OLAP) database stores past data that has been sent in using an OLTP system. An OLAP system allows users to view a variety of summaries of stored multidimensional data.

An OLAP system allows information extraction from a bigger database and analyzes the same with the intent of decision-making. To do so, the system provides support for both simple and complex queries.

The effectiveness of an OLAP system is measured through its response time, and its primary objective is data analysis. In case of a transaction failure, the user can simply rerun the transaction and extract the required details.

Compared to an OLTP system, transactions made with an OLAP system are infrequent. However, OLAP transactions are long and therefore require more processing time and storage space. The tables in an OLAP database are not normalized.

OLAP databases feature aggregated and historical data that is stored in multidimensional schemas. Typically, this is a star schema.

Examples of OLAP transactions include viewing financial and sales reports, extracting budgeting information, and viewing marketing management details. A personalized Amazon homepage with item recommendations are also instances of an OLAP system at play.

Pros:

  • Can easily impose security restrictions on users to comply with regulations and protect sensitive data.
  • Consistency of information as well as calculations.
  • Offers a single platform for almost all types of business analytical needs.

Cons:

  • Dependents heavily on an IT professional or team for implementation and maintenance.
  • Effectiveness depends on the cooperation of interdepartmental personnel.

What is OLTP (Online Transaction Processing)?

Online Transaction Processing (OLTP) systems become the source of data for OLAP systems. The primary purpose of a typical OLTP system is to record current update, insertion, and deletion requests, and modify the extant database accordingly.

OLTP systems support transaction-oriented applications in a 3-tier architecture. They administer the daily transactions of an organization. Data processing is the primary objective of an OLTP system.

Unlike an OLAP database, a typical OLTP database gets updated often. An OLTP transaction might fail before completing, causing serious data integrity issues to the OLTP system. Hence, such an online processing system needs to take special care of data integrity.

OLTP systems maintain data integrity in multi-access environments, and their effectiveness is usually evaluated by the total number of transactions they can carry out in a single second.

A typical OLTP database stores detailed and current data. The Entity Model is the scheme used for storing such transactional databases. Therefore, databases about OLTP systems are normalized. Typically, it is achieved using the 3NF normalization.

Most OLTP queries are simple and short. Hence, they have lesser processing time and storage space requirements. An ATM is the best example of an OLTP system. Other noteworthy examples of OLTP systems include online banking and sending an SMS.

Pros:

  • Useful for day-to-day transactions.
  • Simplifies individual processes, allowing an organization to increase its consumer base.

Cons:

  • Allows multiple users to access and modify the same data, leading to potential issues.
  • Online transactions can be severely affected by hardware failures.

OLAP vs. OLTP: Differences

To simplify the comparison between OLAP and OLTP systems, we have divided the following section into several categories.

1. Backup & Recovery

OLAP systems require backups less frequently. Hence, a strict backup schedule isn’t as important. Some environments might also consider reloading the related OLAP data as a recovery method instead of having regular backups.

The view on backup and recovery is the opposite for an OLTP system. A complete backup at any moment in time is mandatory, along with some kind of provision for incremental backups.

This is because operational data is critical to run a business, and the loss of such data can cause undesired fiscal and legal issues for the concerned organization.

2. Data

Online transactional data serves as the main source of data for an OLTP system. Several databases about multiple OLTP systems come together to act as the chief source of data for an OLAP system.

Data about OLTP systems is operational data, while data related to OLAP systems is consolidation data. The purpose of data for OLTP systems is to control as well as run fundamental business tasks.

For OLAP systems, data intends to assist with planning, problem-solving, and decision-making. Typically, data exposed to OLTP requests are in the form of a screen or screenshot. 

On the contrary, data displayed by OLAP systems are in the form of multidimensional views.

3. Database

An OLTP system is an online database modifying system that relies on traditional database management systems. An OLAP system makes use of the data warehouse concept and is an online database query management system.

While an OLTP database is composed of several tables, a typical OLAP database has fewer tables. It’s optional for tables in an OLAP database, which typically uses the star and/or snowflake schema, to be normalized.

However, this is not the same with tables belonging to an OLTP database. In this case, the tables must be normalized, typically, in 3NF.

4. Data Integrity

An OLTP system frequently executes transactions that modify the database. In case a transaction fails, it can lead to some serious data integrity consequences. Therefore, data integrity can’t be ignored when OLTP systems are concerned.

Unlike OLTP systems, OLAP systems go through infrequent transactions. Therefore, the chance of failing in some transactions is very low. Hence, OLAP systems don’t necessarily require data integrity.

5. Primary Intent

An OLTP system focuses on inserting, updating, and sometimes deleting information from the database. On the contrary, the primary focus of a typical OLAP system is to allow the user to retrieve/extract multidimensional data that can be analyzed and used for decision-making.

While the users make quick inserts and updates to an OLTP system, OLAP systems are characterized by periodic long-running batch jobs and select operations that refresh the data.

6. Storage Space Requirements

The requirement for storage space is small for OLTP systems and even smaller for those systems with archived historical data.

On the contrary, OLAP systems ask for significant storage space. This is due to the existence of aggregation structures and historical data, which calls for many more indexes than a typical OLTP system.

7. System Type

While OLAP is an online data retrieval and analysis system, OLTP is an online transaction system. Unlike the OLAP system, the OLTP system is responsible for managing database modification.

8. Transactions

An average transaction for an OLTP system is short and fast. This is not the case for an OLAP system, where a typical transaction lasts much longer. However, the frequency of transactions is lower for OLAP systems and higher for OLTP systems.

The total processing time required by an OLTP transaction is small. Contrarily, an OLAP transaction requires much time for carrying out a single transaction. This is evident from the fact that response time for OLTP and OLAP systems are measured in milliseconds and seconds or minutes, respectively.

9. Query Complexity

Both OLAP and OLTP systems are query-based. However, queries concerning the OLTP systems are simple as compared to OLAP systems that provide support for complex queries.

A typical OLTP query is relatively standardized and returns a few records. An OLAP query, on the other hand, involves aggregations and returns a heavy load of records or information.

Conclusion

While OLTP systems are apt for administering daily tasks, OLAP systems are great at storing historical data that can be churned later for decision-making and problem-solving. 

As both the OLAP and OLTP online processing systems fulfill different purposes, choosing between them depends entirely on the requirements. Organizations tend to use both OLAP and OLTP, but you use OLAP when you need to gain insight from a lot of data. If you need to manage large amounts of transactions quickly, you use an OLTP system.

Frequently Asked Questions

1. What is OLAP in SQL?

OLAP is used to extract information from a bigger database and analyze it to make decisions. Examples of OLAP transactions include viewing financial and sales reports, extracting budgeting information, and viewing marketing management details. 

2. Is OLAP normalized or denormalized?

Tables in OLAP are not normalized. It doesn't require the atomic details of every transaction so no normalization takes place.

3. Are OLAP and Data Warehouse the Same?

A data warehouse is a repository to store data that can later be used for analysis. OLAP is used to analyze and evaluate data in a warehouse. They are not quite the same.

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Akhil Bhadwal

Akhil Bhadwal

A Computer Science graduate interested in mixing up imagination and knowledge into enticing words. Been in the big bad world of content writing since 2014. In his free time, Akhil likes to play cards, do guitar jam, and write weird fiction. View all posts by the Author

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Dai Software

Nice Blog.
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