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VMware Tanzu Data Services pros and cons

Vendor: VMware
4.0 out of 5
2,914 followers
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Pros & Cons summary

Prominent pros & cons

PROS

Works very well with large database queries
Integrates with modern data science approaches 
Helps achieve large-scale analytics
The loading speed is very good

CONS

If a user consumes a huge load of resources, it takes down the entire system
Compression for GPText could be more efficient.
Needs improvement in memory management 
Lacks sufficient inbuilt machine-learning functions
Maintenance is time-consuming
 

VMware Tanzu Data Services Pros review quotes

Erick  Karanja - PeerSpot reviewer
Apr 11, 2024
Reliability for the messages is key. RabbitMQ ensures your messages are safe. They are not deleted and stuff.
SG
Apr 3, 2024
RabbitMQ provides access to SDKs for development and the ability to raise and log tickets if we encounter issues. We can integrate RabbitMQ using various languages like Java or Python using the provided SDKs.
AF
Jun 21, 2023
The solution's best feature is its exceptional speed, delivering efficient utilization of resources.
Learn what your peers think about VMware Tanzu Data Services. Get advice and tips from experienced pros sharing their opinions. Updated: April 2024.
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Teodor Muraru - PeerSpot reviewer
Dec 27, 2021
Companies can scale the solution, so long as they have server room.
it_user555939 - PeerSpot reviewer
Mar 7, 2018
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.
GB
Oct 18, 2020
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.
AANKITGUPTAA - PeerSpot reviewer
Nov 7, 2022
The solution is stable.
MT
Jan 23, 2021
Some of the most valuable features are publish and subscribe, fanout, and queues.
Jayanta Datta - PeerSpot reviewer
May 10, 2023
Helps us to achieve large-scale analytics.
it_user264192 - PeerSpot reviewer
Aug 24, 2017
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.
 

VMware Tanzu Data Services Cons review quotes

Erick  Karanja - PeerSpot reviewer
Apr 11, 2024
If messages pile up until the space of the memory is full, then basically, the cluster goes down, and someone has to log in through the backend and purge all messages.
SG
Apr 3, 2024
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.
AF
Jun 21, 2023
The support feature could benefit from some improvement in terms of accessibility and responsiveness.
Learn what your peers think about VMware Tanzu Data Services. Get advice and tips from experienced pros sharing their opinions. Updated: April 2024.
771,212 professionals have used our research since 2012.
Teodor Muraru - PeerSpot reviewer
Dec 27, 2021
The user interface could be improved.
it_user555939 - PeerSpot reviewer
Mar 7, 2018
Implementation takes a long time.
GB
Oct 18, 2020
The initial setup is somewhat complex and the out-of-the-box configuration requires optimization.
AANKITGUPTAA - PeerSpot reviewer
Nov 7, 2022
It doesn't have any GUI-based monitoring tools.
MT
Jan 23, 2021
They should improve on the ability to scale your queues in a very simple and elegant way with the same power that they have would be great.
Jayanta Datta - PeerSpot reviewer
May 10, 2023
Lacks sufficient inbuilt machine-learning functions for complex use cases.
it_user264192 - PeerSpot reviewer
Aug 24, 2017
We would like to see Greenplum maintain a closer relationship with and parity to features implemented in PostgreSQL.