Google App Engine vs. Oracle Exadata

App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.

Incentivized

Oracle Exadata is well-suited for environments where massive performance for Oracle databases is required. Storage indexes reduce the unnecessary I/O. Smart Flash
Cache accelerates random reads/writes.

Our OLTP application demands very high concurrency. Multi-node Exadata provides high availability and zero downtime during DB patching. It comes with lots of built-in automations, so it reduces many routine tasks for sysadmins, like network, storage, and VM configuration, and it also reduces many Oracle DBA tasks, like Oracle software installation, patching, and upgrades.

Incentivized

• Quick to develop, quick to deploy. You can be up and running on Google App Engine in no time.
• Flexible. We use Java for some services and Node.js for others.
• Great security features. We have been consistently impressed with the security and authentication features of Google App Engine.

Incentivized

• Oracle Database : Deliver industry-leading security, high availability and scalability with Oracle Database, which has been significantly enhanced to take advantage of the Oracle Exadata Storage Servers.
• Exadata Smart Scan : Improve query performance by offloading intensive query processing and data mining scoring to scalable intelligent storage servers.
• Smart Flash Cache : Transparently cache 'hot' read and write data to fast solid-state storage, improving query response times and throughput. Exadata systems use the latest PCI flash technology rather than flash disks. PCI flash delivers ultra-high performance by placing flash directly on the high speed PCI bus rather than behind slow disk controllers.
• Hybrid Columnar Compression : Reduce the size of data warehousing tables by 10x, and archive tables by 50x, to improve performance and lower storage costs for primary, standby, and backup databases. Query high, query low, archive high and archive low.
• Infiniband Network : Connect multiple Oracle Exadata Database Machines using the InfiniBand fabric to form a larger single system image configuration. Each InfiniBand link provides 40 Gigabits of bandwidth–many times higher than traditional storage or server networks.
• Petabyte Scalability : Easily scale data warehouse to support enterprise data growth.

Incentivized

• There is a slight learning curve to getting used to code on Google App Engine.
• Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
• Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)

Incentivized

• The process of patching and upgrade of Exadata server components could be improved with a goal to minimize the overall effort, make it fully automated and transparent.
• Improved guidelines and possibly more sophisticated tools for sizing of new Exadata servers for migration from old legacy hardware.

Incentivized

App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.

Incentivized

I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster

Incentivized

I am comparing Exadata with the Oracle RAC database experience. In addition to Oracle RAC features, Exadata provides automatic performance optimization through Smart Scan and storage indexes. Deep integration with the Oracle ecosystem and tight coupling with Oracle Enterprise Manager
for monitoring and management. Some downsides of Exadata are: a steep learning curve, concepts like cell offloading, IORM, and flash cache behavior aren’t intuitive initially. Operating
Exadata requires specialized DBA skills.

Incentivized

Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.

Incentivized

We were on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.

Incentivized

Oracle Exadata Database Machine had the best performance overall hands down. It clearly beat the competition and we were seeing 1000X improvement on SAP HANA. Oracle Exadata Database Machine beat that without us refactoring our code. To achieve that in HANA, we had to refactor the code somewhat. Now this was for our limited POC of 5 use cases. Given the large number of stored procedures we had in Sybase, we need to capture more production metrics but we are seeing incredible performance.

Incentivized

• Effective employee adoption through ease of use.
• Effective integration to other java based frameworks.
• Time to market is very quick. Build, test, deploy and use.
• The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.

Incentivized

• Single support from a single vendor with both machine and database from Oracle, which is costing us less.
• With Exadata, we need less technical manpower and less technical support. A business transaction with the integrated and centralized database helps us focus on other business needs.
• We don't need to buy additional licenses and Hardware for the next 3 to 5 years.

Incentivized