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."Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"The performance is pretty good."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"It's open-source, so it's very cost-effective."
"It's good for storing historical data and handling analytics on a huge amount of data."
"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."
"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 most valuable feature for us is horizontal scaling."
"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."
"Pivotal Greenplum's shared-nothing architecture."
"It's super easy to deploy and it also supports different languages and analytics."
"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."
"It works very well with large database queries."
"It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it."
"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."
"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."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."
"It needs better user interface (UI) functionalities."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"The upgrade path should be improved because it is not as easy as it should be."
"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."
"It will be very useful if we could communicate with other database types from Greenplum (using a database link)."
"VMware Tanzu Greenplum needs improvement in the memory area and improved methods for quick access to the disc. So, one of the quick goals of Greenplum must work on enhancing access to the disc by adding hints in the database."
"The installation is difficult and should be made easier."
"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."
"Initial setup is a little complex. It took around two weeks to deploy."
"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."
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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