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The storage system is a critical component of any Oracle database environment. Sizing and configuring a storage system without understanding the requirements can have adverse consequences. This section discusses the types of database workloads and some common tools available to help define the requirements.
An online transaction processing (OLTP) workload typically consists of small random reads and writes. The I/O sizes are generally equivalent to the database block size. The primary goal of designing a storage system for this type of workload is to maximize the number of IOPS while minimizing the latency.
Unlike an OLTP workload, an online analytic processing (OLAP) or decision support system (DSS) workload has a relatively low volume of transactions. Most of the activities involve complex queries and aggregate a large dataset. The volume of data tends to grow steadily over time and is kept available for a longer time. OLAP workloads generally have large sequential reads or writes.
The primary goal of designing a storage system that services this type of workload is to optimize the I/O throughput. The design must consider all components in the entire I/O path between the hosts and the drives in PowerStore. Meeting high-throughput requirements might require having multiple HBAs on the server and adding front-end ports on PowerStore.
Oracle I/O patterns do not always follow a strict OLTP or OLAP pattern because Oracle databases can be designed to service both OLTP and OLAP applications. In cases like this, gather performance metrics and choose a design that provides the best sizing result for mixed workloads.