Most organizations with non-trivial data processing needs—including virtually all medium and large businesses and corporations—rely on enterprise application software (EAS), e.g.,CRM, SCM, and ERP, for their data processing and analysis. These EAS applications generally run on top of a DBMS, which handles the actual storage and retrieval of data. The performance of the underlying DBMS—i.e., its ability to process large amounts of data within an acceptable amount of time—is therefore of crucial importance for providing timely and accurate information to business decision makers using the EAS applications.
As businesses bring more and more data online and adopt more and more sophisticated analyses, the data processing requirements on the underlying DBMS grow correspondingly. However, the amount of time available for data analysis does not grow (the night is still only 12 hours long...) and expectations for system responsiveness do not decrease. EAS and DBMS software are expected to carry out the more sophisticated (and complex) analyses on the larger volumes of data just as quickly, and thus need to increase in performance over time. This means that DBMS performance continues to be a pressing concern for such organizations.
Field specialization increases the performance of the underlying DBMS. As data management is perhaps the major component of EAS performance, a faster DBMS implies a more responsive EAS. That in turn results in greater user efficiency: users don’t have to wait as long for reports to materialize, and can perform more complex business analyses on greater amounts of data. The end result is smoother operations and better business decisions.
Field specialization offers DBMS vendors the opportunity to significantly speed up their DBMS in a manner orthogonal to existing optimization strategies.