Difference between OLTP and OLAP systems. Why should they be separated?

In today's business environment, effective data management and analysis is critical to strategic decision making. In this context, OLTP and OLAP systems play a fundamental role. However, many organisations still do not understand the need to separate these two types of databases. This separation is essential to ensure both operational efficiency and accurate, rapid analysis of information.?

OLTP Database system: The Heart of Operations?

OLTP (Online Transaction Processing) systems are at the heart of a company's daily operations. These databases are designed to handle a high volume of simultaneous transactions, ensuring data consistency, integrity, and real-time availability. Operations such as customer purchases, inventory updates and record entries are stored in the OLTP system.?

The primary focus of the OLTP system is speed and efficiency in managing individual transactions. This system is optimised for fast read and write operations such as inserting, updating and deleting data. However, an OLTP system is not designed for complex analytical queries or managing large amounts of historical data, as this can overload the system and degrade performance.?

OLAP Systems: The Analytical Engine?

On the other hand, OLAP (Online Analytical Processing) is a Business Intelligence tool designed to collect and analyse large volumes of data.? While OLTP handles day-to-day operations, OLAP is designed to run complex queries to discover patterns, identify trends and generate valuable reports for strategic decision-making.?

One of the key benefits of an OLAP system is the ability to gather information from multiple sources. Not only from OLTP, but also from other heterogeneous systems such as CRM, ERP, spreadsheets and external sources using APIs. This integration capability allows data to be pre-processed and made available for analysis, providing a comprehensive view of business performance.??

Why they should be separated systems??

The different objectives and technical requirements make it essential that OLTP and OLAP are separate systems. Using an OLTP system for business intelligence (BI) analysis can overload it and have a negative impact on day-to-day business operations. Complex BI queries are resource-intensive, requiring longer processing times and more resources. This would slow down transactions and affect customer experience, productivity and efficiency.?

Separating these two types of databases ensures that BI queries do not disrupt day-to-day operations. In this way, the OLTP system can continue to perform critical tasks efficiently, while the OLAP system handles analytical processing without impacting operational performance.?

OLAP systems: Data Lakes and other models?

There are different types of OLAP architecture. The most popular are data lakes and data warehouses:?

• Data Warehouse: It is a database specifically designed to analyse large volumes of structured information. This system stores historical data and enables the creation of detailed reports to support informed decision making.?

• Data Lake: Unlike a data warehouse, a data lake stores both structured and unstructured data from multiple sources. It's perfect for organisations that work with raw data and want to perform more flexible and customised analysis.?

Both models provide fast and efficient access to data for BI analysis, ensuring that analytical queries do not impact day-to-day business operations.?

OLAP Advantages?

A dedicated OLAP system not only avoids overloading the OLTP, but also provides several benefits that optimise analysis and decision making:??

• External Data Integration: OLAP system can integrate information from external systems, such as partner APIs, social media and marketing platforms, extending analytical capabilities.?
• Fast and efficient access to data reporting: Pre-processed data stored in an optimised system enables the creation of reports and dashboards, enabling teams to make timely, data-driven decisions.?
• Data centralisation: OLAP system centralises information from across the organisation, facilitating the creation of integrated reports that provide a global view of business performance.?

Conclusion??

Distinguishing between OLTP and OLAP systems not only improves operational efficiency, but also enhances an organisation's analytical capabilities. By keeping the two systems separate, the business can ensure that daily transactions are not impacted by heavy analytical queries, while ensuring that the BI team has fast and efficient access to data, even from external sources. This hybrid architecture ensures a consistent and high-quality flow of data, optimising both operations and data-driven decision making.?

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