Businesses need to respond faster than ever to customer information and demands, which are arriving in rapidly increasing volumes from ever more diverse and distributed systems. This need for real-time business models can not be addressed by traditional integration and business intelligence solutions because streaming analytics and related concepts are central to the solution. The real-time model means responding immediately to new information as it arrives and streaming analytics is at the core of these next generation IT systems.
Increasing the speed of business under these pressures of rapidly increasing data volume and more diverse data sources has been expensive and complex. Rapid responsiveness has proved elusive because real-time needs simply cannot be met by delivering more information faster from historical data. Real-time businesses require distributed technology that provides low latency and high-performance processing of data and event streams. By using continuous, streaming SQL queries, business answers can be generated as soon as input data becomes available. Whereas databases query historical data, streaming SQL queries and transforms data on the wire without any prior staging in a database.
As a result, streaming SQL is complementary to traditional EAI, business intelligence, and data warehousing solutions. By completing real-time processing and analysis before storing the data, streaming SQL delivers reduces the cost of processing rapidly arriving data. Even better, streaming SQL makes existing, in-house SQL skills immediately applicable to real-time analysis, reducing integration time and costs.
To learn more about the Business Case for Streaming SQL, please read our “Concepts in Streaming SQL” mini-white paper.