We performed a comparison between Apache Spark and QueryIO based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop."I found the solution stable. We haven't had any problems with it."
"This solution provides a clear and convenient syntax for our analytical tasks."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"Features include machine learning, real time streaming, and data processing."
"The fault tolerant feature is provided."
"The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly."
"The product’s most valuable features are lazy evaluation and workload distribution."
"The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"Anyone who has even a little bit of knowledge of the solution can begin to create things. You don't have to be technical to use the solution."
"The solution’s integration with other platforms should be improved."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"When you are working with large, complex tasks, the garbage collection process is slow and affects performance."
"At the initial stage, the product provides no container logs to check the activity."
"Dynamic DataFrame options are not yet available."
"The solution needs to optimize shuffling between workers."
"Apache Spark can improve the use case scenarios from the website. There is not any information on how you can use the solution across the relational databases toward multiple databases."
"There needs to be some simplification of the user interface."
Earn 20 points
Apache Spark is ranked 1st in Hadoop with 60 reviews while QueryIO is ranked 16th in Hadoop. Apache Spark is rated 8.4, while QueryIO is rated 8.0. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of QueryIO writes "Stable with good connectivity and good integration capabilities". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas QueryIO is most compared with Splice Machine.
See our list of best Hadoop vendors.
We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
