Features of Online Transactional Processing (OLTP)

Online transactional processing, abbreviated as OLTP, allows huge quantities of people to execute massive numbers of database transactions in real time over the internet.

A database transaction is an operation that modifies, adds, removes, or queries data stored in a database. Many of the daily financial transactions are driven by online transactional processing systems and the database operations they enable, including online banking and ATM transactions, in-person and in-store purchases, and hotel and airline reservations, to mention a few. Each of these situations leaves the database transaction as a record of the associated financial transaction. Password changes and text messages are examples of non-financial database transactions that OLTP can fuel.

In OLTP, the indivisibility of every database transaction serves as its distinguishing feature; a transaction can either pass or fail. It cannot continue to exist in a preliminary or interim stage.

Characteristics of OLTP       

OLTP systems often perform the following tasks:

• Execute a huge amount of basic transactions, often installations, upgrades, and removals of data besides straightforward data searches (for example, a balance check at an ATM).
• OLTP systems rely on concurrency algorithms to make sure that no two users may update the same data at the same time and that all transactions are completed in the right sequence. This allows for multi-user access to the same data while maintaining data integrity. It helps stop users of online reservation services from making duplicate reservations for the same accommodation and safeguards joint account holders from unintentional overdrafts.
• Stress very quick processing with millisecond-level reaction times. The total quantity of transactions that can be processed per second serves as a benchmark for the efficiency of an OLTP system.
• Deliver indexed sets of data. These are employed for quick retrieval, scanning, and inquiring.
• All-time Accessibility. Again, because OLTP systems handle so many concurrent transactions, any loss of data or outage may have a big impact and be very expensive. Every instant must have access to a full data backup. OLTP systems need ongoing incremental backups as well as frequent regular backups.

Difference between OLTP and OLAP

OLTP and OLAP, or online analytical processing, are frequently mixed up. Both systems are online data processing systems with identical acronyms, but that is the only thing they have in common.

OLTP is designed with online database transactions in mind. Frontline employees such as cash registers, bank tellers, and part-time clerks use OLTP systems, which are also made for consumer self-service apps e.g., online banking, e-commerce, and travel reservations.

OLAP is designed with complicated data analysis in mind. OLAP systems serve business intelligence (BI), data mining, and other decision support applications and are intended for usage by data scientists, business analysts, and knowledge workers.

There are several key technological distinctions between OLTP and OLAP systems:

• An OLTP system uses a relational database, which supports quick response times while supporting many concurrent users, frequent queries, and updates. Multidimensional databases, a unique type of database built from numerous relational databases and used by OLAP systems, allow for complicated searches incorporating various data facts from both current and historical data. A data warehouse may be arranged as an OLAP database.
• Simple OLTP queries often only access one or a small number of database entries. Complex OLAP queries with plenty of records are known as OLAP queries.
• OLAP response times are orders of magnitude slower than OLTP transaction and query response times.
• Due to the nature of transactional processing, OLTP systems regularly alter data; OLAP systems never modify data.
• While OLAP workloads are read-intensive, OLTP workloads balance read and write operations.
• OLTP databases need only a small amount of storage capacity, but OLAP databases, which operate with huge data sets, often need a lot of space.
• OLTP systems need regular or simultaneous backups, but OLAP systems can have far less frequent backups.
• OLTP systems frequently act as an information source for OLAP systems. Additionally, the objective of OLAP analytics is frequently to enhance company strategy and streamline business operations, which can serve as a foundation for OLTP system enhancements.

Examples of OLTP Systems

OLTP systems can be found in many systems that are geared toward consumers and in almost every sector or vertical market. OLTP system examples include:

• ATMs and online banking services
• Processing credit card payments
• Order taking (retail and back-office)
• Online reservations (ticketing, reservation systems,)
• Maintaining records (including health records, inventory control, production scheduling, claims processing, customer service ticketing, and many other applications)