Difference Between OLTP and OLAP

OLAP and OLTP are two different systems. OLTP is useful for processing multiple number of transactions. On the other hand, OLAP supports decision support applications.

OLTP and OLAP are two major areas in relational database development. —  The two technologies complement each other, though there might be many differences. In general, the OLTP systems provide source data to data warehouses, while OLAP systems help to analyze it. Let’s discuss the difference between the two systems in this article.

Table of Contents

• What is OLTP?
• What is OLAP?
• Relationship between them
• Benefits
• Drawbacks
• OLTP vs. OLAP

What is OLTP?

Before specifying the differentiating factors, let us understand each of them: OLTP (On-line Transaction Processing) – It is an IT system that processes data transactions. You can find such systems all around you; from an ATM to text messaging through smartphones. In fact, most business applications are these systems. Generally, it is characterized by a large number of short online transactions (INSERT, UPDATE, DELETE). Let us now dive deep into its explanation.

• Data for OLAP systems is obtained via OLTP systems. A typical OLTP system’s main objective is to track current Update, Insertion, and Deletion requests and update the existing database as necessary.
• In 3-tier architecture, OLTP systems support transaction-oriented applications. They oversee an organization’s everyday operations. An OLTP system’s primary goal is data processing.
• A typical OLTP database gets updated often, unlike an OLAP database. The OLTP system may have significant data integrity problems due to an OLTP transaction that fails before it is finished. Therefore, such an online processing system must carefully consider the integrity of the data.
• Detailed and recent data are typically stored in OLTP databases. Such transactional databases are stored using the Entity Model. Databases about OLTP systems are therefore normalized. Usually, the 3NF normalization is used to do this.

Examples-

Most OLTP queries are straightforward and brief. As a result, they demand less processing time and storage space. The ideal illustration of an OLTP system is an ATM. Other notable OLTP system examples include online banking and SMS transmission.

What is OLAP?

OLAP (On-line Analytical Processing) – From the ‘analytical’ part of OLAP, one can understand what this system does: analysis of data efficiently and effectively. It is an approach for handling multi-dimensional queries and works with a large amount of data. In this system, the effectiveness is measured by the response time rather than accuracy as in OLTP.

Let us go through the below points to understand this in-depth-

• An OLTP system’s inputted historical data is stored in an OLAP database. Users of an OLAP system can get various summaries of multidimensional data that has been stored.
• An OLAP system enables data extraction from more extensive databases and data analysis with the goal of decision-making. The system offers support for both simple and complicated queries to achieve this.
• An OLAP system’s efficiency is determined by how quickly it responds, and data analysis is its primary goal. OLTP systems don’t worry about maintaining data integrity. The user may easily re-run the transaction and get the necessary facts in the event of a transaction failure.
• An OLAP system has fewer transactions per day than an OLTP system. But because OLAP transactions are lengthy, they take longer to process and take up more storage. An OLAP database’s tables might not be normalized.
• Multidimensional schemas are used in OLAP databases to hold historical and aggregated data. Usually, a star schema is used for this.

Examples-

Viewing financial and sales reports, gathering data for budgeting, and viewing specifics of marketing management are some examples of OLAP transactions. Another example of an OLAP system is a customized Amazon homepage with suggested items.

Relationship between OLTP and OLAP

It might be difficult and complex to extract helpful information from data collected in OLTP databases. Data must be accessible in specific, defined, valuable forms so that OLAP systems can make the most of it when obtaining a variety of BI-related information, such as forecasts and trends.

Look at the image below that shows the relationship between the two systems.

The above image shows that OLTP and OLAP are complementary procedures rather than opposing approaches to the same problem. OLTP systems often supply the data warehouses with the raw data, whereas OLAP systems assist with data analysis.

The ETL procedure, i.e., Extract, Transform, and Load is essential in tying the two processes together and integrating them. Raw data is retrieved from different sources, cleaned up, and transformed into a standard format before being collected from OLTP systems. Through OLAP systems, analytical tools utilize this data to collect intelligent information.

Using OLTP and OLAP systems on the same server is also conceivable. However, several difficulties can pose a problem. Since OLAP queries are so complicated, direct access by the OLAP database to the OLTP database may cause the system to run slowly. Data that has been denormalized is not present in OLTP. Therefore, dealing directly with OLAP may take a lot of time.

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Benefits of OLTP and OLAP

Both OLTP and OLAP have a variety of advantages and are incredibly valuable to businesses. OLTP and OLAP offer the following advantages:

• To help businesses with budgeting, planning, and forecasting, OLAP offers a one-stop platform that powers business analysis, intelligence, and insights capabilities.
• It is safe, and restricted access and regulatory functions safeguard confidential data.
• It provides reliable data and produces precise calculations.
• OLTP supports daily real-time business transactions.
• It encourages the simplification of numerous concurrently happening individual processes and permits a large number of consumers to use services.

Drawbacks of OLTP and OLAP

Like all systems, OLAP and OLTP have some disadvantages as well. The drawbacks of OLAP and OLTP are as follows:

• Since most tools demand advanced modeling, IT specialists can only utilize OLAP efficiently.
• To use its array of tools successfully requires collaboration between staff members from several departments.
• OLTP systems are less expensive to design than OLAP systems.
• OLTP is a vital component of many sensitive services, and hardware failure can have a negative impact on hundreds of users and transactions.
• Due to the simultaneous access and modification of data by many users, OLTP systems have become more sophisticated.

OLTP and OLAP: Differences

 Let us now dig deeper into the differences between the two systems:

Data Source

OLAP data comes from the various OLTP databases, whereas OLTPs are the original source of data. OLTP data is operational data whereas OLAP data is consolidation data.

Application of data

As data in OLTP is operational, it is used to run and control fundamental business tasks. E.g. Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM). In OLAP, it is used in planning, problem-solving, managing information and decision support.

Users

OLTP users are usually front-end employees or staff. OLAP users are usually managers, executives, data scientists, marketers or business owners.

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Speed

Data processing is fast in OLTP as compared to OLAP, where it depends mainly on the amount of data. In OLTP, there is a requirement for some indexes on large tables, whereas OLAP requires more indexes.

Space requirements

The space requirements in OLTP is relatively smaller than that of OLAP if historical data is archived. However, OLAP requires more space requirements due to the existence of aggregation structures and history data, requiring more indexes.

Updates and data refresh

Updates in the OLTP system are frequent, while in OLAP it is infrequent. Data refresh in OLTP are performed fast and produce immediate results, whereas in OLAP, refreshing of data with huge data sets take time and is sporadic.

Database design

The database of OLTP is highly normalised with many tables and relationships. On the other hand, the database design of OLAP is typically de-normalised with fewer tables and uses star, snowflake or constellation schema.

Data queries

Queries in OLTP are usually standardised and simple, returning relatively fewer records than the OLAP system. OLAP system often has complex queries involving aggregations. Data on the OLTP system is absolutely critical, it has a complex backup system for incremental backups. Since the data in OLAP is relatively less critical than OLTP, full data backup is required only from time to time.

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Though there is a huge difference between the two systems, both of them perform extremely important tasks in their own area. OLTP is more of an operational system whereas OLAP is used for decision-making and other activities that require complex data analysis. Both OLTP and OLAP are corporate information processing systems. Although they have similar names, they serve quite different functions and use different techniques to handle data.

You need to keep in mind that the database structure differs greatly, and the type of optimization required necessitates a different architectural configuration and processing methods. Both are crucial for our organizations because they each have a unique set of characteristics and are trivial to maintain databases.

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