What is Online Transaction Processing (OLTP)? | by Niklas Lang | Jan, 2023
Get to know the difference between OLTP and OLAP
Online Transaction Processing (OLTP) describes the simultaneous processing of several so-called transactions. Transactions include, for example, ATM withdrawals, online banking, or e-commerce sales.
Transaction data is information that accumulates in the environment of organizations and companies. In many cases, these are so-called business transactions, such as incoming or outgoing payments, new orders, or the purchase of raw materials. Transactions are indivisible and consistent.
These properties also coincide with the so-called ACID criteria of databases. Indivisibility (or atomicity in the case of databases) means that transactions are either executed in full or not at all. In other words, they are done or not done at a certain point in time. Consistency describes the property that a transaction always leaves the system in a consistent, i.e. valid, state.
In order to be able to store such transactions in a database, certain requirements are placed on the system (e.g. ACID). In addition, the demand for higher performance, i.e. the simultaneous processing of multiple transactions, has increased steadily in recent years.
Transactional data is therefore treated as a special class of data because it has specific characteristics that distinguish it from other data sets. These characteristics include:
- Normalization: The normalization of transaction data is usually very high. This means that the data must be free of inconsistencies or other anomalies. This is the core data of companies, so there must be no errors, as these can have expensive consequences in the real world.
- Consistency: Transaction data has high requirements for consistency so that incorrect queries cannot cause data to change.
- Data Model: In many cases, transaction data is structured and can therefore be easily converted into a tabular form. Relational databases are therefore ideal for storing transaction data.
Due to the peculiarities of transactional data and their high demands on the databases used, Online Analytical Processing includes all tools specialized for real-time transactional data processing.
In many cases, these are relational databases, since they meet the high requirements of transactions in terms of consistency and normalization. At the same time, relational databases can usually process many queries simultaneously. However, there are also isolated NoSQL solutions that can be used for OLTP.
Online Transaction Processing Systems are characterized mainly by the following points:
- Volume: The volume of users who want to query a large amount of data at the same time is very high. In large companies, in particular, orders are processed by a very large number of people. The system must be able to handle these high loads.
- High Availability: The database cannot afford any downtime, as this has expensive consequences in real life, such as lost sales.
- Simple but frequent Data Modifications: The nature of data modification in OLTP systems is usually very similar and new records are added, such as new orders, or existing records are modified, for example, because a return occurred. However, these modifications can be very common during busy periods, especially in e-commerce stores.
- Fast Response Times: The systems are also frequently used in production operations and must therefore be able to guarantee short response times. For example, if a customer in an online store wants to view his previous orders, the query should happen very quickly so that the loading time of the website is low. Otherwise, a long loading time is perceived by the customer as poor website quality.
- Integrity: As we have already explained, transactions require a high degree of consistency to ensure the truthfulness of the data.
An online transaction processing system has three different levels. The transactions are stored on the lowest level, the so-called data layer.
The business logic layer checks whether transactions are correct and comply with previously defined rules. This is also where it is determined whether all the necessary prerequisites are in place for a transaction to be completed. Finally, the presentation layer represents the front end that the user gets to see.
The terms OLTP and OLAP, which stands for Online Analytical Processing, are often mistakenly interchanged in everyday usage. Although they sound relatively similar, they have little to do with each other.
Online Transaction Processing (OLTP) describes systems that have been optimized to execute transactions, for example of money, quickly and reliably. The focus is on providing users with an easy-to-use program for processing transactions.
Online Analytical Processing (OLAP), on the other hand, is a term from the field of databases and describes a system for easier interpretation of data. OLAP is mainly used by data scientists and business analysts who try to find structures in data.
In addition to this general distinction, much more technical differences can also be found. The following points are taken from an article by IBM:
- OLAP uses big data analysis, while OLTP deals with individual records needed to process transactions.
- The analysis in the field of OLAP has no time pressure and can take several minutes without any problems. OLTP, on the other hand, focuses on fast response times in order to make the user’s transaction as fast as possible.
- OLAP applications work with large amounts of data, which can also often originate from different data sources and must therefore first be merged. With OLTP, on the other hand, the data structures are kept relatively simple and thus comparatively small databases are often sufficient.
The prevalence of OLTP systems is very high, as every business processes transactions in some way. It has experienced another boom due to the rise of e-commerce. Some of the most common applications include:
- ATMs process outgoing payments with the help of OLTP
- Credit Card Transactions
- Incoming Orders in almost all industries
- E-Commerce
- Returns Management
- Online Transaction Processing (OLTP) describes the simultaneous processing of several so-called transactions.
- Transactions have some requirements on the underlying databases, such as high consistency and fast data processing.
- The architecture of OLTP is usually divided into three levels, namely the presentation level, business logic level, and data storage level.
- OLTP and OLAP share much of their name but are very different. The main difference is that OLTP continuously adds new transactions to databases, while OLAP only deals with data analysis.
Microsoft, IBM, and Oracle offer detailed articles on online transaction processing, which were also used as sources for this article:
Get to know the difference between OLTP and OLAP
Online Transaction Processing (OLTP) describes the simultaneous processing of several so-called transactions. Transactions include, for example, ATM withdrawals, online banking, or e-commerce sales.
Transaction data is information that accumulates in the environment of organizations and companies. In many cases, these are so-called business transactions, such as incoming or outgoing payments, new orders, or the purchase of raw materials. Transactions are indivisible and consistent.
These properties also coincide with the so-called ACID criteria of databases. Indivisibility (or atomicity in the case of databases) means that transactions are either executed in full or not at all. In other words, they are done or not done at a certain point in time. Consistency describes the property that a transaction always leaves the system in a consistent, i.e. valid, state.
In order to be able to store such transactions in a database, certain requirements are placed on the system (e.g. ACID). In addition, the demand for higher performance, i.e. the simultaneous processing of multiple transactions, has increased steadily in recent years.
Transactional data is therefore treated as a special class of data because it has specific characteristics that distinguish it from other data sets. These characteristics include:
- Normalization: The normalization of transaction data is usually very high. This means that the data must be free of inconsistencies or other anomalies. This is the core data of companies, so there must be no errors, as these can have expensive consequences in the real world.
- Consistency: Transaction data has high requirements for consistency so that incorrect queries cannot cause data to change.
- Data Model: In many cases, transaction data is structured and can therefore be easily converted into a tabular form. Relational databases are therefore ideal for storing transaction data.
Due to the peculiarities of transactional data and their high demands on the databases used, Online Analytical Processing includes all tools specialized for real-time transactional data processing.
In many cases, these are relational databases, since they meet the high requirements of transactions in terms of consistency and normalization. At the same time, relational databases can usually process many queries simultaneously. However, there are also isolated NoSQL solutions that can be used for OLTP.
Online Transaction Processing Systems are characterized mainly by the following points:
- Volume: The volume of users who want to query a large amount of data at the same time is very high. In large companies, in particular, orders are processed by a very large number of people. The system must be able to handle these high loads.
- High Availability: The database cannot afford any downtime, as this has expensive consequences in real life, such as lost sales.
- Simple but frequent Data Modifications: The nature of data modification in OLTP systems is usually very similar and new records are added, such as new orders, or existing records are modified, for example, because a return occurred. However, these modifications can be very common during busy periods, especially in e-commerce stores.
- Fast Response Times: The systems are also frequently used in production operations and must therefore be able to guarantee short response times. For example, if a customer in an online store wants to view his previous orders, the query should happen very quickly so that the loading time of the website is low. Otherwise, a long loading time is perceived by the customer as poor website quality.
- Integrity: As we have already explained, transactions require a high degree of consistency to ensure the truthfulness of the data.
An online transaction processing system has three different levels. The transactions are stored on the lowest level, the so-called data layer.
The business logic layer checks whether transactions are correct and comply with previously defined rules. This is also where it is determined whether all the necessary prerequisites are in place for a transaction to be completed. Finally, the presentation layer represents the front end that the user gets to see.
The terms OLTP and OLAP, which stands for Online Analytical Processing, are often mistakenly interchanged in everyday usage. Although they sound relatively similar, they have little to do with each other.
Online Transaction Processing (OLTP) describes systems that have been optimized to execute transactions, for example of money, quickly and reliably. The focus is on providing users with an easy-to-use program for processing transactions.
Online Analytical Processing (OLAP), on the other hand, is a term from the field of databases and describes a system for easier interpretation of data. OLAP is mainly used by data scientists and business analysts who try to find structures in data.
In addition to this general distinction, much more technical differences can also be found. The following points are taken from an article by IBM:
- OLAP uses big data analysis, while OLTP deals with individual records needed to process transactions.
- The analysis in the field of OLAP has no time pressure and can take several minutes without any problems. OLTP, on the other hand, focuses on fast response times in order to make the user’s transaction as fast as possible.
- OLAP applications work with large amounts of data, which can also often originate from different data sources and must therefore first be merged. With OLTP, on the other hand, the data structures are kept relatively simple and thus comparatively small databases are often sufficient.
The prevalence of OLTP systems is very high, as every business processes transactions in some way. It has experienced another boom due to the rise of e-commerce. Some of the most common applications include:
- ATMs process outgoing payments with the help of OLTP
- Credit Card Transactions
- Incoming Orders in almost all industries
- E-Commerce
- Returns Management
- Online Transaction Processing (OLTP) describes the simultaneous processing of several so-called transactions.
- Transactions have some requirements on the underlying databases, such as high consistency and fast data processing.
- The architecture of OLTP is usually divided into three levels, namely the presentation level, business logic level, and data storage level.
- OLTP and OLAP share much of their name but are very different. The main difference is that OLTP continuously adds new transactions to databases, while OLAP only deals with data analysis.
Microsoft, IBM, and Oracle offer detailed articles on online transaction processing, which were also used as sources for this article:
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