Google Kubernetes Engine supplies containerized application management powered by Kubernetes which includes Google Cloud services including load balancing, automatic scaling and upgrade, and other Google Cloud services.
$0.04
vCPU-hr Autopilot Mode
Oracle Autonomous Data Warehouse
Score 8.3 out of 10
N/A
Oracle Autonomous Data Warehouse is optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can discover business insights using data of any size and type. The solution is built for the cloud and optimized using Oracle Exadata.
N/A
Pricing
Google Kubernetes Engine
Oracle Autonomous Data Warehouse
Editions & Modules
Autopilot Mode - 3 year commitment price (USD)
$0
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - 1 year commitment price (USD)
$0.0000438
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - Regular Price
$0.0000548
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - Spot Price
$0.0000548
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - Spot Price
$0.0014767
GKE Autopilot Pod Memory Price GB-hr
Autopilot Mode - 3 year commitment price (USD)
$0
GKE Autopilot Pod Memory Price GB-hr
Autopilot Mode - 1 year commitment price (USD)
$0.0039380
GKE Autopilot Pod Memory Price GB-hr
Autopilot Mode - Regular Price
$0.0049225
GKE Autopilot Price GB-hr
Autopilot Mode - Spot Price
$0.0133
GKE Autopilot vCPU Price vCPU-hr
Autopilot Mode - 3 year commitment price (USD)
$0.02
GKE Autopilot vCPU Price vCPU-hr
Autopilot Mode - 1 year commitment price (USD)
$0.0356000
GKE Autopilot vCPU Price vCPU-hr
Autopilot Mode - Regular Price
$0.0445
vCPU Price vCPU-hr
Standard Mode
$0.10
per hour
Cluster Management
$0.10
per cluster per hour
Cluster Management
$74.40 monthly credit
per month per hour
Standard Mode - Free Version
Free
per hour
No answers on this topic
Offerings
Pricing Offerings
Google Kubernetes Engine
Oracle Autonomous Data Warehouse
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Google Kubernetes Engine
Oracle Autonomous Data Warehouse
Features
Google Kubernetes Engine
Oracle Autonomous Data Warehouse
Container Management
Comparison of Container Management features of Product A and Product B
If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.
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.
Engine upgrade rollout strategy - well documented and configurable
Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)
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.
It is very expensive product. But not to mention, there's good reasons why it is expensive.
The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.
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.
Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.
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.
GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.
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
When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.
Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.