The schema is designed to have enough variety and complexity to support a broad range of operations. Although the benchmark is designed with cloud computing in mind, the database schema, data population, and transactions have been designed to be broadly representative of the basic elements most commonly used in OLTP workloads. The benchmark measures the performance of a mix of basic database operations that occur most frequently in online transaction processing (OLTP) workloads. The benchmark and its methodology are described in more detail below. There is no guarantee that any particular database will scale in the same way as the benchmark under increasing load. For example, an IO-intensive application may hit IO thresholds sooner, or a CPU-intensive application may hit CPU limits sooner. In reality, databases are of different sizes and complexity, encounter different mixes of workloads, and will respond in different ways. The goal of the benchmark is to provide a reasonable guide to the relative performance of a database that might be expected when scaling up or down between compute sizes. While the benchmark exercises the same basic operations that are common to all OLTP workloads, it does not represent any specific class of database or application. The benchmark comprises a collection of different transaction types run against a schema containing a range of tables and data types. The transaction rates achieved with the benchmark application will not be the same as those that might be achieved with other applications. It is important to understand that all benchmarks are representative and indicative only. Correlating benchmark results to real world database performance

Physical characteristics (CPU, memory, IO) associated to each DTU measure are calibrated using a benchmark that simulates real-world database workload.

For more information, see manage file space in Azure SQL Database. Under some circumstances, you may need to shrink a database to reclaim unused space.

Deep space 9 elastic reality