With machine learning progressing into the enterprise and bringing with it the ability to utilize every bit of data possible, it is essential to process an increasing amount of data in real-time.
There are a number of applications being developed that make autonomous decisions about where data is produced, consumed, analyzed, and reacted to in real-time. The technology is making pragmatic, tactical decisions on its own as a result.
However, if data is not captured within a certain window of time, its value is lost and the decision or action that needs to take place as a result never occurs.
In this GigaOm report, sponsored by DataStax, you’ll learn about real-time data and how autonomous systems can be fed at scale while producing reliable performance and get an assessment and benchmark of two leading streaming data technologies—Apache KafkaTM and Apache PulsarTM, including their similarities and differences.
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