OLTP
First thing first, what does OLTP means? OLTP stands for Online Transaction Processing and is a database type system very common in the tech industry. It’s mainly used because allows real-time and accurate data processing for a large number of users.
The main difference between this an OLAP Is that the latter is more focused on the analytical side of the data.
OLTP is built to handle lots of requests, information and users doing insertions, updates and deletions of data in the database. One of the things about OLTP is that it’s really important to maintain data integrity and a way to maintain it is through concurrency (No two transactions can happen to the same data at the same time), in that way you make sure that two people can query the same information and get the same result.
Additionally, OLTP uses Indexed datasets to speed up searches and queries. Works with backups so the data is available all the time.
It focuses on transaction speed, with everything designed to ensure the fastest response time between the user and the database
Some people say that OLAP is the evolution of OLTP and in some way it is, but it’s important to understand that they are both different and has different goals, one it’s focused on the transactions and speed and the other one is focused in analytics.
Transactions
Don’t let the word transaction trick you, OLTP is heavily used in banks, e-commerce, ATMs and airlines because of that you may think that it’s meaning is related to the exchange of economics but it’s more related to the computational transactions (it’s the atomic change of state in the database)
Another important aspect is that transactions either succed or fail as a whole; they can’t remain in an intermediate or pending state. This means that for the database, the transaction worked or not, inside the data, economical transaction or business rules, you can have pending states, but in the data flow can’t.
In other words OLTP
- Process larges quantity of transactions.
- Multiple users can access the same data with data integrity.
- Rapid processes, usually measured in milliseconds.
- Uses indexed data sets.
- Has to be available all the time.
In another article I will discuss OLTP vs OLAP as technologies for data.
- Have you worked with OLTP systems before? How do they impact your daily work? Share your thoughts in the comments!
- Want to dive deeper into OLAP vs. OLTP? Stay tuned for my next article where I compare both in detail!
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Top comments (2)
excelente información
As a starter in data science this is super useful to know.