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."With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"We use Spark to process data from different data sources."
"Features include machine learning, real time streaming, and data processing."
"The solution has been very stable."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"This solution provides a clear and convenient syntax for our analytical tasks."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"It provides a scalable machine learning library."
"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 setup I worked on was really complex."
"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."
"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."
"The initial setup was not easy."
"The solution must improve its performance."
"Dynamic DataFrame options are not yet available."
"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."
"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.
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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.
