What is Streaming Analytics Software?
Streaming Analytics is performing analytic computations on streaming data. Data streams can come from devices, sensors, websites, social media, applications, infrastructure systems, and more.
The emergence of the big data revolution means that vast amounts of data are flowing at high velocity, and corporations must process this streaming data in real time to achieve differentiation from their competitors.
Streaming Analytics Features & Capabilities
Real-time data analysis and reporting
Compatible with multiple data sources
Integrated development tools
Automation through machine learning
Uses of Streaming Analytics Software
Streaming analytics is uniquely important in real-time stock-trading analysis by financial services companies. it has also become crucial for real-time fraud detection; data and identity protection services, and analysis of Internet of Things data from sensors embedded in physical objects.
Streaming Analytics vs. Complex Event Processing
This category of tools is an evolution of Complex Event Processing (CEP) software, designed specifically for the big data era. Some of the differences between these two related categories are:
Stream Processing Engines tend to be distributed while CEP engines tend to be more centralized
Stream Processing Engines require custom code while CEP engines often have a SQL like a query language.
CEP engines are tuned for low latency and often they respond within few milliseconds while Stream Processing engines take close to a second to generate results.
Some companies elect to build their own solutions using sometimes components like message brokers, stream processing engines, data extraction tools, and more. However, the degree of expertise required to build easy-to-use scalable platforms can be daunting. For this reason, many prefer to purchase end-to-end platforms. These products are often provided as cloud services and pricing plans vary, making direct comparison difficult. Some products charge users by streaming units consumed and the amount of data processed. Other vendors charge by usage hours.