There is a cost associated with putting your data to work, and the benefits you gain depend on the systems you put into place. To maximize net value, you need to strike a balance between minimizing costs and maximizing gain.
Kafka’s challenges have exhausted many an engineer on the path to successful data streaming. What if there was an easier way?
The applications for real-time data processing are diverse and far-reaching. This article highlights just a few.
Real-time and batch are two broad categories of data processing. Though they handle data differently, both are vital to the systems that make our businesses and society run.
