Amazon Web Services vs. Google Cloud Platform

We are using RDS for the database services. With RDS, we don't have to manage much, as most of the DBA tasks are automated. For development purposes, we are using Kubernetes pods, which makes it easy to deploy applications and scale up as needed. AWS integration with in-house applications is seamless, making it easy to keep a data-sensitive application on-premises while still utilizing AWS services.

Incentivized

For how it helps our team with data storage and connecting to GA4 as a backup option, and the incredibly low cost for us to use it and reliably back up our data, I would highly recommend using this tool for all of your cloud storage needs. It's easy to use and their customer service is always responsive and easy to get a hold of.

Incentivized

• Starting an instance and accessing it for testing purpose, demo or production deployment its always easy.
• All the things which are available over AWS are pretty well managed and easy to use.
• You might find everything you required for an product and other development over AWS.
• Its suitable for both either an enterprise or an startup
• Various resources and documentation are available in case you struck somewhere.

Incentivized

• Google Cloud Platform provide the autoscale workload when the workload need to scale up or down
• Great pay-as-you-go pricing model and dashboard report of pricing that help user monitor and optimize the cost
• Using simpler than other cloud provider

• The AWS Management Console can be overwhelming. so a better dashboard and organizing it would improve usability.
• The pricing models are complex. We need a more clear price calculators and cost management tools to manage our expenses better.
• Enhancements in cross service compatibility and easier third party integrations could streamline workflow.
• Simplifying model training in SageMaker and improving IAM for granular access control would make AWS more user friendly

Incentivized

• The Logs Explorer is quite hard to dig into and find logs of interest
• BigQuery transparency for BigLake vs External tables isn't the best
• Google Group management for permissions can get hairy.

Incentivized

I would gladly rely on AWS for any large-scale application deployment. For prototyping and small-scale applications, a more heavily managed environment on top of the 'bare metal' virtual infrastructure, such as Heroku or Elastic Bean Stalk, is probably a more productive approach in most cases

Amazon Web Services is a great tool when it comes to middle size organizations like us. It provides multiple tools and functionalities in low costs. The best feature we have to pay as we go. No financial burden on company for the unused instances. It also comes with greater level of security such as two level authorization such as multi factor authorization.

I've found it incredibly easy to use since day one of deployment.

Incentivized

Availability is very good, with the exception of occasional spectacular outages.

AWS does not provide the raw performance that you can get by building your own custom infrastructure. However, it is often the case that the benefits of specialized, high-performance hardware do not necessarily outweigh the significant extra cost and risk. Performance as perceived by the user is very different from raw throughput.

The customer support of Amazon Web Services are quick in their responses. I appreciate its entire team, which works amazingly, and provides professional support. AWS is a great tool, indeed, to provide customers a suitable way to
immediately search for their compatible software's and also to guide them in a
good direction. Moreover, this product is a good suggestion for every type of
company because of its affordability and ease of use.

Incentivized

The API's were very well documented and was Janova's main point of entry into the services.

In my personal experience, AWS is superior to both GCP and Azure in the majority of usable applications. GCP suffers from the near total misunderstanding of how support system is even supposed to work, and while _some_ services are pretty nifty and well-polished, some are mindbogglingly designed black boxes with self-conflicting documentation. Some of it comes from having legacy systems, sure, but AWS somehow manages, even having a rather big lead start. Azure, from my limited experience, is limited to people somehow coerced into its usage by external constraints. That being said, IF you can design and implement something there, it will probably run fine.

Incentivized

I feel GCS buckets are pretty interchangeable with Amazon S3 as far as I have typically used them. It just depends on who or your company wants to give money to. I have liked the Google Cloud Platform BigQuery console better than the interface for Snowflake, but that may be due to familiarity and the proportion of time I've used Google Cloud Platform over Snowflake.

Incentivized

• Provisioning resources like large database instances is really quick. We can easily scale our instances up or down as per need.
• Storing files in S3 instead of onprem NAS drives is much more economical, especially for the files stored in glacier deep archive for compliance purposes.
• Backup snapshots of EBS volumes and RDS instances may increase the cost of cloud if not cleaned up properly.

Incentivized

• Approx 30% cost savings after moving from on-prem to GCP due to reduced hardware, maintenance of DC support, and energy costs.
• There are much faster release cycles due to CI/CD pipelines with cloud build and scalable infrastructure using GKE. It works very nicely.
• We use BigQuery a lot, and what used to take hours now takes minutes, speeding up business decisions across teams. Clients.

Incentivized