Data processing is a very diverse field with countless applications that power modern digital enterprise platforms and end-user apps. One of the most common data processing techniques is online transaction processing. This data management system utilizes extensive access layering to form a tiered process of accessing and writing information to and from databases. Online transaction processing is one of the most common data management systems due to its diverse functionality. Here is a detailed breakdown of online transaction processing.
What is online transaction processing?
Online transaction processing was primarily a data management system for physical enterprise systems like ATMs, POS machines, and recordkeeping systems. As time went by and digital transformation started permeating other types of data exchanges, online transaction processing (OLTP) grew. The exchange of data between end-user interfaces and databases is transactional in nature, and thus a lot of online applications and enterprise systems utilize OLTP solutions.
In most cases, this data management system leverages relational databases to process insights accurately and sequentially. The main idea behind OLTP systems is to execute transactions using the intended data without skipping a step within the process. This makes online transaction processing the ideal solution for transactions requiring the same data set at the same time. In a nutshell, OLTP can be shortly described as a data processing solution designed for the trade of data, money, services, or information.
Distributed online transaction processing
The OLTP process is a distributed form of data processing that leverages multiple nodes to compute insights between end-user interfaces and databases. Using a distributed operational data store to power transactional enterprise systems and applications has a lot of benefits. If insights are required by multiple end-user applications at the same time, or data sets are used by several users simultaneously, this tends to impact the app’s UX.
To power these complex applications with tiered data access layers to grant multiple user interfaces with the insights they need, distributed OLTP is the answer. Data management engineers and architects design transactional enterprise solutions accordingly and leverage distributed online transaction processing to power enterprise systems and applications.
Benefits of OLTP systems
The main goal organizations have is to acquire more customers without putting much strain on their enterprise systems. Data management plays a pivotal role in ensuring that end-users do not cause system failures if traffic increases. Attaining more customers is contingent on attracting more traffic and increasing transaction processing capacity.
OLTP systems process transactions on websites and applications instead of directly accessing databases. An operational data store with OLTP technology stores the operational insights required to complete the transaction in sequential order. This helps accurately complete transactions without the added latency of querying data directly from databases. Digital transactions are completed in record time by minimizing latency to a minimum.
Reliability and concurrency
Although speed is of the essence, reliability in digital transactions is very important. For example, online transactions like e-commerce purchases need to follow a certain order. If a step is skipped within the process, the e-commerce platform or end-users might not get their end of the bargain. At the same time, an unreliable data processing system for digital transactions could be exploited easily.
Since OLTP uses relational databases, the data processing is done concurrently. Therefore, a transaction won’t be complete if one of the steps in the process is not fulfilled. Implementing distributed OLTP data stores ensures that data is not entered twice in the event of a system failure. Instead, operational insights on the distributed data store can be used to fulfill the transaction even if the main in-memory unit fails.
Is online transaction processing scalable?
Enterprise system developers aren’t only concerned about speed and reliability but also scalability. With that being said, are OLTP solutions scalable? Most OLTP data store vendors provide this solution as a cloud-based SaaS or IaaS offering. SaaS and IaaS offerings have the common benefit of being easily scalable. Organizations using cloud-based solutions are not limited by hardware, which allows them to scale whenever needed to the extent necessary at that time.
Online transaction processing is highly scalable, and the memory units used for this data management system can facilitate large amounts of unprecedented traffic. This has the benefit of facilitating high volumes of transactions during peak seasons. Therefore, enterprises can service seasonal customer demand without facing system failure by using online transaction processing solutions.
Relationship of OLTP and OLAP
OLTP is often compared with OLAP, which stands for online analytics processing. Although these solutions are different data processing systems, comparing them side-by-side is not a fair comparison. Each of these solutions is very useful to holistic data management and can be leveraged to improve business operations. OLTP primarily focuses on processing the operational insights required for completing transactions.
The operational data could be user profiles, product information, banking details, and so forth. All this information is required to process transactions, but it can be reused by being processed through an OLAP system. An OLAP system can reuse the data from OLTP solutions to generate BI reports and provide further insight into customers and market trends. Both these systems can be used collectively in an elaborate data management system for business success.
Real-life applications of OLTP solutions
As mentioned above, some of the traditional applications of OLTP solutions include enterprise systems such as ATMs, bank teller interfaces, etc. These were the initial digital transactions that could be executed, but with rapid digital transformation, the landscape has changed.
OLTP solutions are now used for applications such as online shopping, subscription-based services, and even for downloading some files. For example, digital bookstores require OLTP solutions when customers download an eBook. Additionally, video streaming services also require OLTP solutions due to the architecture of this type of digital platform.
Implementing this data processing technique
Data processing using OLTP has diverse applications, and your enterprise could require a versatile system like this one. How can enterprises implement OLTP systems? Choosing an ODS and in-memory computing SaaS or IaaS vendor that leverages OLTP data processing can power complex enterprise systems or applications.
A data management architect can assist with putting together a viable processing system utilizing all legacy and cloud-based databases you might be using. This could be part of a more elaborate Enterprise Data Warehouse system leveraging disparate sources and powering several applications simultaneously.