Oracle Autonomous Data Warehouse vs. VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

II would recommend Oracle Autonomous Data Warehouse to someone looking to fully automate the transferring of data especially in a warehouse scenario though I can see the elasticity of the suite that is offered and can see it is applicable in other scenarios not just warehouses.

Incentivized

VMware Tanzu Data Services will work perfectly well if you need to run machine learning, deep learning or statistical methods on huge workloads of structured, but also unstructured data. It will be super easy to deploy especially if you are using AWS as your Cloud platform provider. On the other hand, it might be an overkill if you are working with smaller data volumes e.g. gigabyte scale.

Incentivized

• Very easy and fast to load data into the Oracle Autonomous Data Warehouse
• Exceptionally fast retrieval of data joining 100 million row table with a billion row table plus the size of the database was reduced by a factor of 10 due to how Oracle store[s] and organise[s] data and indexes.
• Flexibility with scaling up and down CPU on the fly when needed, and just stop it when not needed so you don't get charged when it is not running.
• It is always patched and always available and you can add storage dynamically as you need it.

• Apache MADlib provides popular machine learning functionality.
• Allows you to query terabytes of data databases.
• Interoperability for AWS S3 is effortless.

Incentivized

• Level of integration or compatibility to connect it to different applications can be improved
• The support service is slow
• The issue is with the record number limitation of not being able to bring back more than one million records or not being able to export larger datasets to Excel

Incentivized

• Slightly more complicated to run on Azure
• Integration with Kafka could be more straight forward
• Extensive support exists only for R and Python

Incentivized

Because

• It is really simple to provision and configure.
• Does not require continous attention from the DBA, autonomous features allows the database to perform most of the regular admin tasks without need for human intervention.
• Allows to integrate multiple data sources on a central data warehouse, and explode the information stored with different analytic and reporting tools.

Incentivized

They were very helpful. We needed support for initial implementation.

Incentivized

Understanding Oracle Cloud Infrastructure is really simple, and Autonomous databases are even more. Using shared or dedicated infrastructure is one of the few things you need to consider at the moment of starting provisioning your Oracle Autonomous Data Warehouse.

Incentivized

As I mentioned, I have also worked with Amazon Redshift, but it is not as versatile as Oracle Autonomous Data Warehouse and does not provide a large variety of products. Oracle Autonomous Data Warehouse is also more reliable than Amazon Redshift, hence why I have chosen it

Incentivized

According to our assessment VMware Tanzu Data Services is one the most capable and efficient data warehouse solutions. Compared to its competitors it was designed from scratch to support the largest possible business intelligence workloads. The fact that it is based on PostgreSQL open source technology is a huge benefit allowing to avoid vendor lock-in, which is not really feasible for other data warehouse platforms.

Incentivized

• With OBIEE we had a limitation on the license, with OAC and Oracle Autonomous Data Warehouse, since it is pay-per-use services, it significantly reduced the cost.
• the resource requirement was also on smaller side, as the maintenance activity primarily was done by the Oracle Autonomous Data Warehouse itself.

Incentivized

• There was a noticeable reduction in system reliability.
• Saw a reduction in unsuccessful analytics operations.

Incentivized