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."AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"Apache Spark can do large volume interactive data analysis."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"I found the solution stable. We haven't had any problems with it."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"The product’s most valuable features are lazy evaluation and workload distribution."
"The deployment of the product is easy."
"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."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"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 logging for the observability platform could be better."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"The setup I worked on was really complex."
"Apache Spark's GUI and scalability could be improved."
"There needs to be some simplification of the user interface."
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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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