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Both online transaction processing systems (OLTP) and online analytical processing systems (OLAP) are used for categorizing and processing data. However, despite their similar names and general purpose, they’re actually quite different.
With just the acronyms OLTP and OLAP, it’s very easy to get them confused and not see the differences between the two of them. It all lies with the one letter – or rather, word – the difference between the two.
An OLTP system is created to be able to process and update information quickly. It’s most often used in retail to keep up with purchases, check and verify credit cards, and, in some cases, track inventory. Hence the ‘T’ for transaction. These systems are streamlined, nimble, and updated in real time.
An OLAP system, on the other hand, is used in data analysis. Typically used for data marts or other data storage systems, it’s a way to sift through and analyze data that’s stored there. These systems aren’t built to be quick but instead analytical powerhouses.
Key Takeaways:
| Online Transaction Processing System (OLTP) | Online Analytical Processing System (OLAP) |
|---|---|
| Has a normalized data model. | Has a denormalized data model – usually a star or snowflake schema. |
| An OLTP system is built to be quick and responsive, often overwriting information rapidly. | An OLAP system is built to be able to analyze large amounts of data as needed, so response time can be a few minutes to an hour or more. |
| These systems are updated in real time, often from multiple fronts. The majority of users are able to alter and overwrite data. | The data is usually updated on a schedule, as having the bleeding edge data isn’t always a necessity. Most users won’t be able to make alterations to the data. |
| It is most often used in retail or ATMs where there are large numbers of transactions in short order. | Most often used in data analysis, mining, and business intelligence. OLAP is often used in data warehouses to help users sort through and analyze the data. |
What Is an Online Transaction Processing System (OLTP)?
An OLTP system has to be able to process data quickly. They’re most often used for transactions such as retail sales and ATMs in order to streamline and keep track of the process. They need to be able to update data constantly and keep their integrity.
Because of that, they’re built to be sleek, keeping excess and duplicate data to a minimum. They also need to be able to handle errors and multiple different changes in data from several locations.
For instance, a bank may have a central system for all the ATMs in a town, and if two different people are using two different ATMs, the system has to be able to track and alter the data to reflect that.
Due to the fact that OLTP are meant to be quick, they have a simpler data model type than OLAP systems do. Most often, it’s a normalized mode, such as Boyce-Codd Normal Form (BCNF). While that sounds complex, the resulting chart ends up looking a great deal like a flow chart – though it has several tables.
You would end up with a chart that has inventory in one box, orders in another (or goods to be purchased), and then the final table links the two together. Of course, with multiple transactions in different locations, the table ends up being a great deal more complex, but the basic form is simple and straightforward.
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What Is an Online Analytical Processing System (OLAP)?
An OLAP system is a system that is used for data analysis, hence the ‘A,’ which stands for analytical. OLAP systems are excellent for data mining and other complex analytical calculations, such as business intelligence and sales forecasting.
Most systems of this type have what’s called an OLAP cube, so-called because it allows you to work with interdimensional data. While that sounds like poor science fiction, data dimensions are a way of categorizing data. Most data is going to have several different aspects to it, such as car sales for a dealership.
The data in a case like this will be divided by time, such as what quarter they were sold in, price range – how expensive the car sold was – and what model it was. It can even be more complex, comprising all of the Ford dealers in the continental United States, and therefore, the region may be included.
Each of these forms parts of the “cube.” The different data connected to one another, allowing you to build a three-dimensional bar graph of sorts. This system allows for queries into different aspects of sales or as a way to pull them together for analysis.
OLAP systems aren’t built to be slow; however, speed isn’t of the essence like it is in an OLTP system. Therefore, queries can take an hour or more to get a response to, though it’s more likely to be a matter of minutes unless you’re working with a huge database or a very complex calculation.
Due to the higher complexity of an OLAP system, it typically uses a star schema or snowflake schema. Unlike the normalized database model that OLTP systems use, the star or snowflake schemas are so named because they resemble those shapes.
There’s the main box with core information in it, and then other boxes split off it, forming a rough star or snowflake shape, adding additional data.
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Di has been a writer for more than half her life. Most of her writing so far has been fiction, and she’s gotten short stories published in online magazines Kzine and Silver Blade, as well as a flash fiction piece in the Bookends review. Di graduated from Mary Baldwin College (now University) with a degree in Psychology and Sociology.
