Which architecture model allows businesses to perform analytics without affecting operational systems?

The architecture model that allows businesses to perform analytics without affecting operational systems is Hybrid Transactional/Analytical Processing (HTAP). This model is designed to handle both transactional and analytical workloads, enabling companies to perform real-time analytics on operational data. By integrating both types of processing, HTAP ensures that data can be accessed and analyzed quickly and efficiently without interfering with the performance of the operational systems that manage data transactions.

This capability is crucial for businesses that require immediate insights from their data, especially in environments where timely decision-making is vital. HTAP systems can capture data in real-time as it is generated from transactional processes and allow analytical queries to be run simultaneously. This dual functionality supports analytics directly on operational data without the need for complex ETL (extract, transform, load) processes or significant data duplication, which can slow down system performance.

Other architecture models, such as Data Warehousing, typically focus on batch processing and involve separate systems for transaction processing and analytics, which can lead to delays and impact performance. While Data Lakehouse models combine the benefits of data lakes and warehouses, they primarily address storage and scalability rather than real-time transactional analytics. Multidimensional databases are used more in the context of OLAP (Online Analytical Processing) scenarios but still rely