We performed a comparison between Microsoft Parallel Data Warehouse, Vertica, and VMware Tanzu Greenplum based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse."It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time."
"Collecting the data through SSIS packages from different sources and putting them all in one data repository is the most powerful thing. While others have this feature, they don't have the simplicity or ease of use when getting a resource and knowing everything about it."
"It is a very stable database."
"The most valuable feature for me is querying."
"It is a stable solution...It is a scalable solution."
"The most valuable features are the performance and usability."
"The data transmissions between the data models is the most valuable feature."
"I like Data Warehouse's data integrity features. Data integrity is what databases are made for as opposed to spreadsheets."
"The feature I like best is performance. We use Red Tool and Red Job for the data warehouse and reporting. It's perfect. Performance is good, and it can return ad hoc queries very quickly. Of course, it's a cluster, so it's easy to scale."
"The performance is very good and the aggregate records are fast."
"I appreciate the flexibility offered by Vertica's projections. It allows for modifying the primary projection without altering the tables, which helps to optimize queries without the need to modify the underlying data."
"We are able to integrate our Vertica data warehouse with Tableau to create numerous reports quickly and efficiently."
"Its projections and encoding are excellent tools for tuning large volumes."
"It maximize cloud economics for mission-critical big data analytical initiatives."
"Integrated R and geospatial functions are helping us improve efficiency and explore new revenue streams. "
"Allows us to take volumes and process them at a very high speed."
"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."
"A very good, open-source 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."
"Pivotal Greenplum's shared-nothing architecture."
"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."
"Helps us to achieve large-scale analytics."
"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."
"It's super easy to deploy and it also supports different languages and analytics."
"They need to incorporate a machine learning engine."
"The solution is expensive and has room for improvement."
"The only issue with the product is that the process is very slow when we have a huge amount of data."
"I would like to see better visualization features."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"The query is slow if we don't optimize it."
"The product does not have all of the features that the native products have."
"Concurrent queries are limited to 32, making it more of a data storage mechanism instead of an active DWH solution."
"Documentation has become much better, but can always use some improvement."
"We faced some challenges when trying to use the temporary tables feature."
"In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform."
"I believe the installation process could be streamlined."
"The documentation of Vertica is an area with shortcomings where improvements are required."
"Limitations in group by projections is where I would like to see an improvement."
"If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer."
"There are a lot of limitations within this product and it makes things extremely hard for developers. It lacks Stored Procedure, packages, and triggers like other RDBMs."
"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."
"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."
"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."
"Extra filters would be helpful."
"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."
"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."
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