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."The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"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."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"The best thing about this solution is that it is very powerful and very cheap."
"Data ingestion: It has rapid speed, if Apache Accumulo is used."
"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 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."
"The loading speed is very good."
"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."
"Very fast for query processing."
"It's super easy to deploy and it also supports different languages and analytics."
"Tanzu Greenplum's most valuable features include the integration of modern data science approaches across an MPP platform."
"It's one of the fastest databases in the market. It's easy to use. From a maintenance perspective it's a good product. The segmentation, or architecture of the product is different than other databases such as Oracle. So even in 10 years, the data distribution for such segments will not affect other segments. The query performance of the product, for complex queries, is very good. It has good integration with Hadoop."
"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."
"The load optimization capabilities of the product are an area of concern where improvements are required."
"Hadoop's security could be better."
"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."
"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."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"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."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"We would like to see Greenplum maintain a closer relationship with and parity to features implemented in PostgreSQL."
"If you have a user consuming a huge load of resources, it takes down the entire system."
"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."
"Maintenance is time-consuming."
"Lacks sufficient inbuilt machine-learning functions for complex use cases."
"Extra filters would be helpful."
"They should add more analytics. Their documentation could also be improved so that I don't have to bother my co-workers and tech support so often."
"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."
Apache Hadoop is ranked 5th in Data Warehouse with 32 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 "A file system for data collection that contains needed information and files". 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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