Management of Memory in the Real Time Data Streams

Real time data streams[11] or streaming of data has become popular in the field of Data science. Data size is growing fast and large whereas it has become challenge for the researchers and industries on managing the data. Real time analysis involves large volume of dynamic data with dynamic change in nature. Once the data is received, correctness of the data needs to be checked. Data mining[19] is the multi-disciplinary field that combines statistics, machine learning[2], Artificial intelligence[10] and database technology. The main characteristic of mining complex data streams is the huge volume of continuous incoming infinite data; the nature of the data is fast-changing and requires a fast real-time response. The data will be of multi-Dimensional. Data sets are complex in nature, main challenge lies on the unbound memory required to store the data and use the same for further analysis. This paper discusses about managing the real time data with available memory and the technologies used for handling it