Last updated 4 years ago
Cloudera bought DataPad because data sci...
Cloudera’s embrace of Apache Spark as a framework for running a majority of future big data jobs speaks to this strategy, as well. Users don’t just like Spark because it’s faster than MapReduce, they also like it because it’s easy to program and supports the Java, Scala and Python languages. This will be especially beneficial for projects such as Cloudera Oryx
Architectural Patterns for Near Real-Tim...
Evaluating which streaming architectural pattern is the best match to your use case is a precondition for a successful production deployment. The Apache Hadoop ecosystem has become a preferred platform for enterprises seeking to process and understand large-scale data in real time. Technologies like Apache Kafka, Apache Flume, Apache Spark, Apache Storm, and Apache Samza are increasingly pushing the envelope on what is possible. It is often tempting to bucket large-scale streaming use cases ...
8 Common Hadoop Projects and Spark Proje...
Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. Apache Hadoop and Apache Spark fullfil this need as is quite evident from the various projects that these two frameworks are getting better at faster data storage and analysis. Check out for 8 common Hadoop and Spark projects.