We performed a comparison between QueryIO and Spark SQL based on real PeerSpot user reviews.
Find out what your peers are saying about Cloudera, Apache, Amazon and others in Hadoop."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."
"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."
"The performance is one of the most important features. It has an API to process the data in a functional manner."
"The solution is easy to understand if you have basic knowledge of SQL commands."
"It is a stable solution."
"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."
"Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline."
"Data validation and ease of use are the most valuable features."
"The stability was fine. It behaved as expected."
"There needs to be some simplification of the user interface."
"Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users."
"This solution could be improved by adding monitoring and integration for the EMR."
"There should be better integration with other solutions."
"In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper."
"I've experienced some incompatibilities when using the Delta Lake format."
"In the next release, maybe the visualization of some command-line features could be added."
"It would be beneficial for aggregate functions to include a code block or toolbox that explains its calculations or supported conditional statements."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
Earn 20 points
QueryIO is ranked 16th in Hadoop while Spark SQL is ranked 4th in Hadoop with 14 reviews. QueryIO is rated 8.0, while Spark SQL is rated 7.8. The top reviewer of QueryIO writes "Stable with good connectivity and good integration capabilities". On the other hand, the top reviewer of Spark SQL writes "Offers the flexibility to handle large-scale data processing". QueryIO is most compared with Splice Machine, whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, SAP HANA, HPE Ezmeral Data Fabric and Netezza Analytics.
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.