We performed a comparison between Amazon EMR and VMware Tanzu Greenplum 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."The solution helps us manage huge volumes of data."
"Amazon EMR is a good solution that can be used to manage big data."
"This is the best tool for hosts and it's really flexible and scalable."
"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."
"The project management is very streamlined."
"The initial setup is pretty straightforward."
"When we grade big jobs from on-prem to the cloud, we do it in EMR with Spark."
"The solution is pretty simple to set up."
"Scalable (Massive) Parallel Processing (MPP) – The ability to bring to bear large amounts of compute against large data sets with Greenplum and the EMC DCA has proven itself to be very effective."
"Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible."
"We chose Greenplum because of the architecture in terms of clustering databases and being able to have, or at least utilize the resources that are sitting on a database."
"The loading speed is very good."
"The most valuable feature for us is horizontal scaling."
"Very fast for query processing."
"Helps us to achieve large-scale analytics."
"A very good, open-source platform."
"There is no need to pay extra for third-party software."
"The product must add some of the latest technologies to provide more flexibility to the users."
"The most complicated thing is configuring to the cluster and ensure it's running correctly."
"Amazon EMR can improve by adding some features, such as megastore services and HiveServer2. Additionally, the user interface could be better, similar to what Apache service provides, cross-platform services."
"The initial setup was time-consuming."
"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."
"Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."
"There is room for improvement in pricing."
"Lacks sufficient inbuilt machine-learning functions for complex use cases."
"If you have a user consuming a huge load of resources, it takes down the entire system."
"I saw some limitation with respect to the column store, and removing this would be an improvement."
"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."
"Maintenance is time-consuming."
"It will be very useful if we could communicate with other database types from Greenplum (using a database link)."
"Tanzu Greenplum's compression for GPText could be made more efficient."
"Implementation takes a long time."
Amazon EMR is ranked 9th in Cloud Data Warehouse with 20 reviews while VMware Tanzu Greenplum is ranked 9th in Data Warehouse with 36 reviews. Amazon EMR is rated 7.8, while VMware Tanzu Greenplum 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 VMware Tanzu Greenplum writes "Very efficient at large scale analytics; lacks inbuilt machine-learning functions for complex use cases". Amazon EMR is most compared with Snowflake, Cloudera Distribution for Hadoop, Azure Data Factory, Amazon Redshift and Apache Spark, whereas VMware Tanzu Greenplum is most compared with Oracle Exadata, Vertica, Oracle Database Appliance, Apache Hadoop and Snowflake. See our Amazon EMR vs. VMware Tanzu Greenplum 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.
