DigitalOcean vs Google Compute Engine: What are the differences?
Developers describe DigitalOcean as "Deploy an SSD cloud server in less than 55 seconds with a dedicated IP and root access". We take the complexities out of cloud hosting by offering blazing fast, on-demand SSD cloud servers, straightforward pricing, a simple API, and an easy-to-use control panel. On the other hand, Google Compute Engine is detailed as "Run large-scale workloads on virtual machines hosted on Google's infrastructure". Google Compute Engine is a service that provides virtual machines that run on Google infrastructure. Google Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run up to thousands of virtual CPUs on a system that has been designed from the ground up to be fast, and to offer strong consistency of performance.
DigitalOcean and Google Compute Engine belong to "Cloud Hosting" category of the tech stack.
Some of the features offered by DigitalOcean are:
- We provide all of our users with high-performance SSD Hard Drives, flexible API, and the ability to select to nearest data center location.
- SSD Cloud Servers in 55 Seconds
- We provide a 99.99% uptime SLA around network, power and virtual server availability. If we fail to deliver, we’ll credit you based on the amount of time that service was unavailable.
On the other hand, Google Compute Engine provides the following key features:
- High-performance virtual machines- Compute Engine’s Linux VMs are consistently performant, scalable, highly secure and reliable. Supported distros include Debian and CentOS. You can choose from micro-VMs to large instances.
- Powered by Google’s global network- Create large compute clusters that benefit from strong and consistent cross-machine bandwidth. Connect to machines in other data centers and to other Google services using Google’s private global fiber network.
- (Really) Pay for what you use- Google bills in minute-level increments (with a 10-minute minimum charge), so you don’t pay for unused computing time.
"Great value for money", "Simple dashboard" and "Good pricing" are the key factors why developers consider DigitalOcean; whereas "Backed by google", "Easy to scale" and "High-performance virtual machines" are the primary reasons why Google Compute Engine is favored.
DigitalOcean, BlaBlaCar, and Accenture are some of the popular companies that use DigitalOcean, whereas Google Compute Engine is used by 9GAG, Snapchat, and CircleCI. DigitalOcean has a broader approval, being mentioned in 943 company stacks & 686 developers stacks; compared to Google Compute Engine, which is listed in 592 company stacks and 427 developer stacks.
What is DigitalOcean?
What is Google Compute Engine?
Want advice about which of these to choose?Ask the StackShare community!
What are the cons of using Google Compute Engine?
I started using DigitalOcean back in January to host a Ghost blog. I was a little worried at first because I didn't have too much experience setting up servers. There was always the option of a full service company that does all the work for you, but the point was that I wanted more control for the purpose of learning. And, learning turned out to be really easy thanks to the great community at DigitalOcean. There are tutorials for just about anything. It has been an amazing learning experience, and now I'm looking forward to hosting more complex projects here. I already have a couple in the works for the near future. I highly recommend it.
I can't rate the Support great or bad, as I haven't really had a need to contact them yet. But everything else has been excellent so far.
I am a freelancer and a researcher. I have had tried a lot of hosting services over the years. But DIgitalOcean stands out from the rest for its pricing. Its just five dollar a month for a basic node.
And the other reason for loving Digital Ocean is that they support Docker. It you buy a VPS machine, chances are that docker support wont be available as with PV or hypervisor, docker need some extra config.
So far I am loving DO :-)
I use Google Compute Engine instances as flexible, reproducible infrastructure that scale with my data science tasks.
Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
I use DigitalOcean for testing or hosting my apps. You can set up an Ubuntu server in less than a minute. There are also one-click-install apps, so I don't have to install e.g. the LAMP stack myself. The dashboard has a really easy UI and is easy to use. The costs begin at 5 bucks per month. Also DigitalOcean has a great support and an adorable community. They have a great support page with hundreds of tutorials.
- I use Google Compute Engine instances as flexible, reproducible infrastructure that scales with my data science tasks.
- Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
- Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
DigitalOcean offers us everything we need to test out specific scenarios or we expect from small-servers like our monitoring-system. We also use digital-ocean in long-term and are very satisfied with their performance and scalability.
If not using managed hosting services like Heroku, AWS Lambda, or Google Cloud Functions, used to host programs because of ease of use and low cost.
Generally used less recently for these use cases than managed hosting services.
Because I like having more control of my deployment, I am currently hosting this on DigitalOcean. I don't need to worry about arbitrary row limits and I can be sure that the app is always running.
We use DigitalOcean to host our build tools (namely Drone.io) for a cheap CI and CD server.
We'll be using this to host the server application during alpha phase.
Been hosting with them for a while now. Never had an issue, great support, great docs: can't beat 'em. Though I'd probably move to AWS for large scale projects.
Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.