VMAX or XtremIO


Primary function of a Data Warehouse is to improve an organization’s ability to understand business information, which is often spread out among disparate systems in the business. Common uses for data warehouses are supply chain, logistics and manufacturing processes and tend to be all inclusive of the business.

A data warehouse is designed to enable business intelligence activities through query and analysis of data from months or years. They usually contain such historical data from multiple data sources. Data warehouses are heavily read-oriented in nature, which enables excellent analytical performance and avoids impact to transactional systems by segregating the workload away from the OLTP environment.

As the amount and types of data continue to increase, data warehouses have to analyze larger amounts of data from an increasing number of sources to provide the business intelligence required. And, they have to do it faster to provide value in today’s Internet speed business environment.

Understanding the customer requirements around read only vs. read/write workloads, scalability of performance and capacity, and SLA’s to the business are all important factors in platform choice. Achieving the desired SLAs often result in compromises for many customers – such as constant tuning of databases, materialized views, multiple indexes, splitting data into multiple copies and data marts, and less data ingested and used for reporting and analysis.

For customers where performance or simplification of the environment is a key requirement, Shared External NVM Fabrics, is the correct choice for this workload because the high levels of performance provided will satisfy SLAs while eliminating the need for constant database tuning and workarounds. For customers that want improved performance but do not need the levels of performance provided by Shared External NVM Fabrics architecture, a tightly coupled scale-out architecture is the correct choice for this workload.

The Spider Chart below shows the distribution and weighting of the primary workload requirements for this use case.