There are quite a few real-time platforms out there. A lot of them are newcomers, and the differences between them aren’t clear at all. The least we can do, is present all the options for you to choose from, so here are five real-time streaming platforms for Big Data.
Welcome to Xplenty's Blog
All things data
Big Data consultant David Gruzman answered some of our burning questions about which Big Data platform to use, whether streaming is a must or not, and what are the biggest issues with the cloud.
Is Apache Spark as hot as you think it is? Although it shines so bright across the Big Data galaxy that some folks think that it may have killed the MapReduce star, Spark is still in its teenage years and has yet to fully mature as a platform. To find out the current state of Spark, we talked to Big Data specialist Uzy Hadad, founder of Inroid.
On paper, Spark and Tez have a lot in common: both possess in-memory capabilities, can run on top of Hadoop YARN and support all data types from any data sources. So, what’s the difference?
Apache Spark is setting the world of Big Data on fire. With a promise of speeds up to 100 times faster than Hadoop MapReduce and comfortable APIs, some think this could be the end of Hadoop MapReduce. Or is it?
Hadoop YARN may be the gun that hangs on the wall in the first act and kills MapReduce in the last—Google Trends clearly shows that interest in Hadoop is still on the rise, but Apache Spark is closing in fast.