AWS V/S Google Cloud Platform
Google Cloud Platform rapidly adds new products. The important thing to note is that while AWS does offer a plethora of services, many of them are niche-oriented and only a few are essential for any project. And for these core features, we think Google cloud is a worthy competitor, even a hands-down winner sometimes, though many of the essential features, like PostgreSQL support, are still in beta in GCP.
Google Cloud can compete with AWS in the following areas:
Cost-efficiency due to long-term discounts: For example, a 2 CPUs/8GB RAM instance will cost $69/month with AWS, compared to only $52/month with GCP (25% cheaper). As for cloud storage costs, GCP’s regional storage costs are only 2 cents/GB/month vs 2.3 cents/GB/month for AWS. Additionally, GCP offers a “multi-regional” cloud storage option, where the data is automatically replicated across several regions for a very little added cost (total of 2.6 cents/GB/month).
Big Data and Machine Learning products
Instance and payment configurability: GCP is a lot more flexible when it comes to instance configuration. Along with predefined instance types similar to AWS, GCP also allows you to customize how many CPUs and how much RAM to use. For example, instance type n1-standard-1 comes with 1 CPU and 3.75GB RAM, but you can choose to have an instance with 1 CPU and, say, 1.75GB of RAM. Or 4.25GB. Or 5GB. You get the idea. If your compute needs fit between the available machine types, a custom machine type can result in significant price reductions. Both AWS and GCP announced a pay-per-second billing model. Starting October 2nd, 2017, AWS will implement a pay-per-second billing for Linux VMs. And starting September 26th, 2017, GCP will offer pay-per-second billing for all VM types and OSes. Furthermore, GCP provides a better approach to discounted long-term usage: Instead of requiring users to reserve instances for long periods of time as AWS does, GCP will automatically provide discounts the longer you use the instance — no reservations required ahead of time.
Here is a comparison of VMs that fall into similar categories across providers, such as high memory, high CPU, SSD storage, etc.