Spark's in-memory computations makes it suparfast over traditional Map-Reduce jobs.

Also spark has capacity to not just read from hdfs but also from any storage. Spark streaming is best for streaming applications.

Dataframes are also the best part of spark. Review collected by and hosted on G2.com.

There is nothing as such to dislike about spark. Review collected by and hosted on G2.com.

In memory computation and storage levels

GRAPHX and sparkmlib to execute ML jobs in distributed env

Support for multiple languages Review collected by and hosted on G2.com.

Performance issues for NON scala udfs

Not able to self optimise skewness Review collected by and hosted on G2.com.

Everything was very perfect. It was a great experience overall. All the things were properly in place. Review collected by and hosted on G2.com.

Nothing as such. Everything was perfect. Review collected by and hosted on G2.com.

Spark is a great tool to work with . I used it for monitoring my systems. Review collected by and hosted on G2.com.

Nothing as of now. Will try to work more and provide a great set backs Review collected by and hosted on G2.com.

Open source frameworks focused on interactive query Review collected by and hosted on G2.com.

Spark has no file management system of its own . Review collected by and hosted on G2.com.

Resilient distributed dataset makes it immutable and fault tolerance. Review collected by and hosted on G2.com.

Spark does not having its own file manager. Review collected by and hosted on G2.com.

Earlier we were using mapreduce and just shifted to spark. It's in memory processing makes it super fast.It's data frame API and also spark streaming is best part of spark. Review collected by and hosted on G2.com.

There is no such thing to dislike about spark. Review collected by and hosted on G2.com.

Easy to use, can support multiple libraries. Review collected by and hosted on G2.com.

Sometimes, sparks run slow,small file issue Review collected by and hosted on G2.com.

Spark is one of the useful tools for cloud architecture. Review collected by and hosted on G2.com.

Spark is not a lot user friendly and needs proficiency to use Review collected by and hosted on G2.com.

Spark helps in Big Data Processing. With its in memory calculations and various other optimizations, it makes Big Data Processing way faster than the traditional Hadoop Big Data System. Review collected by and hosted on G2.com.

Spark configuration is complicated and getting the optimized Spark Cluster Configuration can be hard to get right. Also, due to In Memory calculations, there can be Out of Memory errors. Review collected by and hosted on G2.com.