We performed a comparison between Amazon EMR 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."This is the best tool for hosts and it's really flexible and scalable."
"The solution is scalable."
"The solution helps us manage huge volumes of data."
"The project management is very streamlined."
"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."
"Amazon EMR's most valuable features are processing speed and data storage capacity."
"The solution is pretty simple to set up."
"The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions."
"The search function is the most valuable aspect of the solution."
"The solution is reliable and stable, it fits our requirements."
"The solution is stable."
"We also really like the Cloudera community. You can have any question and will have your answer within a few hours."
"Provides a viable open-source solution for enterprise implementations and reliable, intelligent data analysis."
"The data science aspect of the solution is valuable."
"Customer service and support were able to fix whatever the issue was."
"The most valuable feature is Kubernetes."
"The dashboard management could be better. Right now, it's lacking a bit."
"As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data."
"There is no need to pay extra for third-party software."
"There is room for improvement in pricing."
"The problem for us is it starts very slow."
"The legacy versions of the solution are not supported in the new versions."
"The product must add some of the latest technologies to provide more flexibility to the users."
"We don't have much control. If we have multiple users, if they want to scale up, the cost will go and increase and we don't know how we can restrict that price part."
"The areas of improvement depend on the scale of the project. For banking customers, security features and an essential budget for commercial licenses would be the top priority. Data regulation could be the most crucial for a project with extensive data or an extra use case."
"Currently, we are using many other tools such as Spark and Blade Job to improve the performance."
"While the deployed product is generally functional, there are instances where it presents difficulties."
"There are better solutions out there that have more features than this one."
"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 is not always completely stable in some cases, which can be a concern for big data solutions."
"The procedure for operations could be simplified."
"There is a maximum of a one-gigabyte block size, which is an area of storage that can be improved upon."
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Amazon EMR is ranked 3rd in Hadoop with 20 reviews while Cloudera Distribution for Hadoop is ranked 2nd in Hadoop with 47 reviews. Amazon EMR is rated 7.8, while Cloudera Distribution for Hadoop is rated 8.0. The top reviewer of Amazon EMR writes "Provides efficient data processing features and has good scalability ". 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". Amazon EMR is most compared with Snowflake, Azure Data Factory, Amazon Redshift, Apache Spark and Microsoft Azure Synapse Analytics, whereas Cloudera Distribution for Hadoop is most compared with HPE Ezmeral Data Fabric, Apache Spark, MongoDB, Cassandra and InfluxDB. See our Amazon EMR vs. Cloudera Distribution for Hadoop report.
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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.
