We performed a comparison between Microsoft Parallel Data Warehouse and VMware Tanzu Data Services 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 data transmissions between the data models is the most valuable feature."
"One of the most important features is the ease of using MS SQL."
"The solution's integration is good."
"I like Data Warehouse's data integrity features. Data integrity is what databases are made for as opposed to spreadsheets."
"Microsoft Parallel Data Warehouse integrates beautifully with other Microsoft ecosystem products."
"We are able to monitor daily jobs, so if there is anything that needs to be done then we can do it."
"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."
"We have complete control over our data."
"A very good, open-source platform."
"The product's feature of data transaction works fast."
"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."
"Tanzu Greenplum's most valuable features include the integration of modern data science approaches across an MPP platform."
"After creating a RabbitMQ service, they provide you with a sort of web management dashboard."
"It can be configured to be a very fast message broker. I like the stability, the built-in admin tools and plugin architecture."
"The product has been stable and I have never faced any kind of problems with it."
"Very sophisticated routing control and priority messaging capabilities"
"The only issue with the product is that the process is very slow when we have a huge amount of data."
"It could offer more development across the solution."
"We find the cost of the solution to be a little high."
"The product must provide more frequent updates."
"I would like to see better visualization features."
"I would like the tool to support different operating systems."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"We'd like to see it be a bit more compatible with other solutions."
"The installation is difficult and should be made easier."
"The solution needs improvement on performance."
"Extra filters would be helpful."
"Maintenance is time-consuming."
"Their implementation is quite tricky. It's not that easy to implement RabbitMQ as a cluster."
"The debugging capabilities and testing flexibilities need to be improved."
"Implementing a circuit breaker scenario using RabbitMQ is complicated. This complexity arises because manual intervention is required to manage worker details and handle operations based on worker IP addresses."
"The product needs to focus on offering more use case documentation because browsing the internet to find it can be a process filled with struggles."
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Microsoft Parallel Data Warehouse is ranked 9th in Data Warehouse with 32 reviews while VMware Tanzu Data Services is ranked 5th in Data Warehouse with 81 reviews. Microsoft Parallel Data Warehouse is rated 7.6, while VMware Tanzu Data Services is rated 8.0. The top reviewer of Microsoft Parallel Data Warehouse writes "An easy to setup tool that allows its users to write stored procedure, making it a scalable product". On the other hand, the top reviewer of VMware Tanzu Data Services writes "Reliable queueing functionality and versatile tool that can be used with any programming languages ". Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA and Snowflake, whereas VMware Tanzu Data Services is most compared with IBM MQ, Anypoint MQ, Apache Kafka, Red Hat AMQ and ActiveMQ. See our Microsoft Parallel Data Warehouse vs. VMware Tanzu Data Services report.
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We monitor all 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.
