Review of VMware Tanzu Data Services.
Rating: 8 out of 10
IncentivizedUse Cases and Deployment Scope
We use VMware Tanzu Data Services across the board anytime we need to do analytics on massive data volumes, and by massive we mean up to petabyte size. The most common use case is evaluating data intake from IoT-enabled automated doors or cargo docks, which always necessitates the usage of a database structure.
Pros
- Apache MADlib provides popular machine learning functionality.
- Allows you to query terabytes of data databases.
- Interoperability for AWS S3 is effortless.
Cons
- Running on Azure is a little more difficult.
- Synchronization with Kafka may be a little easier.
Likelihood to Recommend
If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.