We performed a comparison between Apache Spark and Cloudera Distribution for Hadoop based on real PeerSpot user reviews.
Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We use Spark to process data from different data sources."
"This solution provides a clear and convenient syntax for our analytical tasks."
"Apache Spark can do large volume interactive data analysis."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"The product is useful for analytics."
"The most valuable feature of Apache Spark is its ease of use."
"There's a lot of functionality."
"Provides a viable open-source solution for enterprise implementations and reliable, intelligent data analysis."
"It has the best proxy, security, and support features compared to open-source products."
"The solution is reliable and stable, it fits our requirements."
"The solution is stable."
"The most valuable feature is Kubernetes."
"The scalability of Cloudera Distribution for Hadoop is excellent."
"The search function is the most valuable aspect of the solution."
"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there are a lot of things that need to improve. I believe they are working on that."
"It should support more programming languages."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"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."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."
"The solution must improve its performance."
"The competitors provide better functionalities."
"The security of this solution could be improved. There should also be a way to basically have a blockchain enabled storage with the HDFS."
"The solution is not fit for on-premise distributions."
"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there is a lot of things that need to improve."
"Cloudera Distribution for Hadoop has a limited feature list and a lot of costs involved."
"I would like to see an improvement in how the solution helps me to handle the whole cluster."
"The tool's ability to be deployed on a cloud model is an area of concern where improvements are required."
"The governance aspect of the solution should be improved."
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Apache Spark is ranked 1st in Hadoop with 60 reviews while Cloudera Distribution for Hadoop is ranked 2nd in Hadoop with 47 reviews. Apache Spark is rated 8.4, while Cloudera Distribution for Hadoop 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 Cloudera Distribution for Hadoop writes "Good end-to-end security features and we like that it's cloud independent". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and AWS Lambda, whereas Cloudera Distribution for Hadoop is most compared with Amazon EMR, HPE Ezmeral Data Fabric, MongoDB, Cassandra and ScyllaDB. See our Apache Spark vs. Cloudera Distribution for Hadoop report.
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