Abstract
This ESG Technical Review documents our audit of InterSystems IRIS Data Platform performance testing. Tests were executed in a proof of concept environment, with comparisons of three common databases. Testing focused on performance of common queries run in the financial services industry.
The Challenges
Data drives both transactional and analytical business processes. Transactions with customers and partners define revenue and profit, while analyzing data—whether from customers and suppliers or from sensors and machines—provides key insights to inform business decisions. The ability to transform real-time data into knowledge to make business decisions can be the difference between success and failure. Data management technologies must provide a strong foundation for analytics, and must be easily deployed, cost efficient, scalable, and most of all, high performing; delays bog down answers and business transformation. When ESG asked IT decisions makers about their data management challenges, performance was most often cited, followed by security and control issues, data quality, cost, and meeting real-time requirements.
Most organizations leverage multiple databases, adding both infrastructure and staffing costs. If organizations can reduce the footprint required to handle all their transactional and analytics workloads (including real-time, historical, natural language processing, and business intelligence), they can save money. But they must deliver high performance, along with data durability, scalability, and management ease.