We performed a comparison between Amazon EMR and Apache Hadoop based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."
"The initial setup is straightforward."
"The solution is pretty simple to set up."
"We are using applications, such as Splunk, Livy, Hadoop, and Spark. We are using all of these applications in Amazon EMR and they're helping us a lot."
"The solution is scalable."
"The project management is very streamlined."
"It has a variety of options and support systems."
"The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"One valuable feature is that we can download data."
"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics."
"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"The most valuable feature is the database."
"The best thing about this solution is that it is very powerful and very cheap."
"There is no need to pay extra for third-party software."
"There is room for improvement in pricing."
"Modules and strategies should be better handled and notified early in advance."
"Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."
"The initial setup was time-consuming."
"The product must add some of the latest technologies to provide more flexibility to the users."
"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."
"The problem for us is it starts very slow."
"Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"I would like to see more direct integration of visualization applications."
"The solution is very expensive."
"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"It would be good to have more advanced analytics tools."
"It could be more user-friendly."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
Amazon EMR is ranked 9th in Cloud Data Warehouse with 20 reviews while Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews. Amazon EMR is rated 7.8, while Apache Hadoop is rated 7.8. The top reviewer of Amazon EMR writes "Provides efficient data processing features and has good scalability ". On the other hand, the top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". Amazon EMR is most compared with Snowflake, Cloudera Distribution for Hadoop, Azure Data Factory, Amazon Redshift and Apache Spark, whereas Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata. See our Amazon EMR vs. Apache Hadoop report.
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We monitor all Cloud Data Warehouse 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.