When it comes to designing your data strategy, you have several options for where you can store your data and how it will be processed. Two that you’ll likely hear about are the OLAP (online analytical processing) and OLTP (online transactional processing) databases, and whether or not they should exist in the same place. To understand why they are different, let’s look at how each one is used.
Modern Applications Requires Multiple Databases
Businesses need to analyze data in order to find insights that can improve their operations. This is where databases come into play. One type, called OLAP (online analytical processing), is used to process large amounts of data quickly in order to generate reports for decision-making purposes.
The other type, called OLTP (online transaction processing), handles the transactions. These two types of databases have different purposes so it's important that they are separated from each other so there isn't a conflict between them.
For example, an OLAP database has no need for changes since all it does is store and retrieve data. On the other hand, an OLTP database needs to be updated with changes made on a regular basis because these databases track records as they happen.
What is an OLAP Database
OLAP stands for Online Analytical Processing, which is a type of database that can provide fast analytical data with complex calculations. OLAP databases are designed to be queried by users who want to slice and dice the data in a variety of ways, including time periods, locations, product categories, or other variables. As opposed to relational databases which require all the information to be stored in one place. This allows for faster retrieval times when retrieving data because it only needs to retrieve one section at a time rather than the entire dataset.
What is an OLTP Database
OLTP databases are used to store the data that is being actively used by a system, typically in real-time, as opposed to a data warehouse that stores aggregated or historical data. The main advantage of having an OLTP database is its speed. When your system needs to access the data, it will be able to do so quickly. This makes it perfect for systems that need fast retrieval such as ERP systems, CRM systems, transactional websites, Financial applications etc.
You typically do not want to combine OLAP and OLTP use cases on the same servers as it can severely impact the performance of applications using the OLTP database
How are they different?
OLAP databases are designed for analytics, reporting, and querying. OLTP databases are designed for transactional operations such as storing data from point-of-sale systems, customer support tickets, or other business transactions. Generally speaking, analysts don't need access to the transactional data in an OLTP database. But they often do need access to the data stored in an OLAP database.
If both OLAP and OLTP databases reside on the same server, it becomes challenging to balance workloads between them while still providing necessary data protection. If there's a system outage that affects the availability of one type of database, you can have downtime in two separate functions that rely on it. To prevent this problem, many companies separate their OLAP and OLTP databases by placing them on different servers.
Benefits to separating your databases
There are many benefits to separating your OLAP and OLTP databases. One major advantage is that the two types of databases have different requirements, so they can be optimized for their specific usage pattern. For example, an OLAP database may not need to have a high write-scaling, but it does need to read data very quickly. On the other hand, an OLTP database will require high write-scaling in order to process large amounts of transactions.
Separation of these duties will lead to a superior experience when using and developing applications
Drawbacks to separating your databases
Though there are some drawbacks to separating your databases, the advantages usually outweigh them. With a separate database, you can focus your data analysis on data that is relevant to your business. You won't need to worry about performance issues with an OLAP database if you're only using it for reporting purposes.
Similarly, you won't have to work around any performance limitations of your OLTP database if it's not being used for reporting purposes. As long as you ensure that they are properly secured, both types of databases will be running efficiently and separately when they are being used properly.
CockroachDB is a modern SQL Database that focuses on OLTP workloads that require Scale, Resilience, Consistency and Locality