Yes, Amazon offers a bigger variety of products, but the newer ones just scream vendor lock-in without much-added benefit. Why would I use Opsworks if Chef or Ansible work just as well?
Choose anything, except maybe object storage, and there is somebody out there who does it better than Amazon, there is also sombody who does it cheaper than Amazon.
Except for S3, AWS isn't the best at anything, nor the cheapest, but, they are the only ones doing it all, and typically the ones inovating new services. Nobody has all the services AWS has, or even as well integrated, or as granular etc...
If you have very specific needs, then go pick and choose from different vendors (assuming you're ok with multi-site latency), but if you're starting a company and have generic needs that aren't well defined yet, AWS is probably your best bet to start with. People do that, and once their invested so much time in learning the environement, they stick to it.
AWS has been diligently moving up the stack, creating higher level services that are "good enough" for many of their customers, who are increasingly enterprises teams who want to outsource as much as possible to Amazon. They can go all-in with AWS and expect a constant stream of new features and services at relatively competitive prices.
With Google, their cloud platform still feels non-core to their business and they have a history of retiring services when their priorities change. I hope Google and Microsoft become fully viable alternatives, but for now, enterprises seem more comfortable betting on AWS.
My personal experience has been exactly the opposite - AWS is light years ahead of Google Cloud. Does Google Cloud provide Machine Learning service?
For the longest time, it was only supporting Java and Python SDKs. And the Google's API is still very much lacking in terms of features and stacks. In fact the better support and much comprehensive services presents more choices rather than "vender lock-in". Keep in mind, all the auxiliary services are simply the open source technologies builds on top of AWS EC2 - if you like to spend time and money, you can totally build your own!
And this is common, as we've just seen people complain about Google Cloud 4 days ago.
I do like Google's new DB. It is like an easy to use spark w/ cassandra backend, all behind the scenes. Very nice.
Doesn't Amazon's mysql api fronted db work similar to google's?
For scalability, RDS gives you up to 3TB storage (1TB for SQL Server, 64TB for Aurora) and DB instances with up to 244GB RAM, 32 vCPUs and 10Gigabit network, whereas it looks like Google Cloud SQL is 100GB and 16GB of RAM. It looks like Cloud SQL provides managed replication/failover as standard; with AWS this is optional, but simple to set up. (I use RDS; never tried Google Cloud SQL.)
(I have no connection with either company, beyond being a customer.)
Yes they do. [0]
> And this is common, as we've just seen people complain about Google Cloud 4 days ago.
To me, this is an isolated incident. On the other hand, seemingly every AWS customer of non-trivial size had to reboot a significant part of their machines in the last year because of Xen vulnerabilities (with no way to predict if you will land on a patched machine).
> To me, this is an isolated incident.
http://www.davidmturner.com/2013/07/26/gce-io-performance-su...
Apart from that, noisy neighbors happen on any cloud platform, and as the author of the article said, those test were far from scientific.
I personally don't know why one would use any of the GCE/AWS/Azure ML offerings apart for really small use cases (in which case you probably don't have enough data). Most businesses with an ML component (like my startup) need millions of predictions per day which would be crazy expensive on any of those platforms.
You are describing Google App Engine circa 2010. I recommend taking another critical look at what Google has available because it's quite competitive these days :)