The persistence could be better. Although ESP is designed for in-memory processing, it would be better if the solution is enhanced or improved on the persistence of the data that is kept in the memory. For example, if one server goes down and the information is stored in the memory, it is lost. Therefore, the persistence needs to be improved so that if there are more cases where the server is down, the information and data can still be intact.
Streaming Analytics is crucial for processing real-time data to enhance decision-making and operational efficiency. It empowers businesses to derive actionable insights from continuous data streams.As organizations handle increasing volumes of data, Streaming Analytics solutions provide the tools to analyze and act on data in motion immediately. These solutions are designed to integrate with diverse data sources, applying algorithms and rules that allow for instant insights and responses....
The persistence could be better. Although ESP is designed for in-memory processing, it would be better if the solution is enhanced or improved on the persistence of the data that is kept in the memory. For example, if one server goes down and the information is stored in the memory, it is lost. Therefore, the persistence needs to be improved so that if there are more cases where the server is down, the information and data can still be intact.