We performed a comparison between Apache Hadoop and VMware Tanzu Greenplum based on real PeerSpot user reviews.
Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming."
"It's open-source, so it's very cost-effective."
"Data ingestion: It has rapid speed, if Apache Accumulo is used."
"The tool's stability is good."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"One valuable feature is that we can download data."
"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."
"A very good, open-source platform."
"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."
"With VMware Tanzu Greenplum, one can make a huge database table and analyze the queries by adding in the SQL command. Some hint or command for the query goes over the multi-parallel execution."
"It works very well with large database queries."
"The parallel load features mean that Greenplum is capable of high-volume data loading in parallel to all of the cluster segments, which is really valuable."
"Helps us to achieve large-scale analytics."
"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."
"The loading speed is very good."
"The upgrade path should be improved because it is not as easy as it should be."
"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."
"It would be good to have more advanced analytics tools."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."
"they need to interact more with customers. They need to explain the features, especially when there are new releases of Greenplum. I know just from information I've found that it has other features, it can be used to for analytics, for integration with Big Data, Hadoop. They need to focus on this part with the customer."
"One of the disadvantages, not a disadvantage with the product itself, but overall, is the expertise in the marketplace. It's not easy to find a Greenplum administrator in the market, compared to other products such as Oracle."
"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."
"Lacks sufficient inbuilt machine-learning functions for complex use cases."
"We would like to see Greenplum maintain a closer relationship with and parity to features implemented in PostgreSQL."
"Tanzu Greenplum's compression for GPText could be made more efficient."
"They need to enhance integration with other Big Data products... to integrate with Big Data platforms, and to open a bi-directional connection between Greenplum and Big Data."
"Extra filters would be helpful."
Apache Hadoop is ranked 5th in Data Warehouse with 33 reviews while VMware Tanzu Greenplum is ranked 9th in Data Warehouse with 36 reviews. Apache Hadoop is rated 7.8, while VMware Tanzu Greenplum is rated 7.8. The top reviewer of Apache Hadoop writes "Handles huge data volumes and create your own workflows and tables but you need to have deeper knowledge". 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". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Amazon Redshift, whereas VMware Tanzu Greenplum is most compared with Oracle Exadata, Vertica, Oracle Database Appliance, Snowflake and Teradata. See our Apache Hadoop vs. VMware Tanzu Greenplum report.
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