Top 10s Cloud Compute debriefing

We recently release our Top 10 for Cloud Compute North America and Europe. With the help of our automated platform we tested near to 20 cloud providers and selected the most interesting per region. These studies outline performance/price value of Cloud Computes and bound Block Storages. We focus on maximum performance delivered by general purpose infrastructures, their associated costs and where is the best efficiency per dollar spent.


For each provider, we tested 4 sets of VMs:

Category CPU RAM Extra storage
Small 2 4 100
Medium 4 8 150
Large 8 16 200
XLarge 16 32 500

From all the performance and pricing data we collected, the vendor selection was agnostically done, only by numbers with the following key metrics:

  • Hourly price
  • CPU Multi-thread performance
  • Volume IOPS
  • Volume bandwidth

Inherent biases

1. Hourly prices

De facto, most of the hyperscalers are penalized by the documents’ approach. Despite they could propose computing power at the edge of technology, the design of our subject doesn’t take in account the long term billing options such as 1 year or 3 years. These options are only proposed by big players such as Alibaba, AWS or Azure and you can consider up to 60% of discount if you subscribe to them.

2. Volume throttling

Next, hyperscalers generally throttle volume performance, where small and medium size vendors let you reach 3GB/sec and/or 1MIOPS with block storage, the big players stop around 3000 IOPS. This may seem low but it is guaranteed, where the possible 1MIOPS are neither stable nor predictable.

3. Compute focused

Finally, documents focus on compute: virtual machines and volumes, but cloud providers have so much to propose and especially big players. Server-less, Object Storage, DBaaS, with the variety of existing services, the whole value of a cloud vendors cannot be just about Cloud Compute.

Our insights at a glance

For those who don’t want to read the reports, here’s a small list of the leading providers:

Provider Price Compute Storage Region
Hetzner Very aggressive Average Average Europe
Kamatera Low Average High Worldwide
UpCloud Average High Guaranteed very high Worldwide
Oracle Cloud Average Average High Worldwide

What next ?

These documents will be renewed and their methodology improved. We want to bring more infrastructure characteristics like network and RAM. In the pursuit of objectivity, we think that we must diversify our reports to answer real life problematics such as:

  • Small and medium size providers
  • Hyperscalers
  • Country based
  • Provider origin based
  • Object storage, CDNs, DBaaS, Kubernetes, etc

We also want to digitalize this kind of report. Instead of just PDF, we wish to let consumer explore data with a web application. This will also let user appreciate more than 10 vendors without decrease reading quality.

For the meantime, do not hesitate take a look at our document center.


Out of the wood #1 : Kamatera

That’s make almost 3 years our analysis platform runs on computers all around the globe and automagically collects stuff about cloud market such as locations, instance sizes and more important price and performance. We are actually close to 60 providers, counting IaaS, PaaS or CDNs as vendors and this is a huge stack of knowledge that we want to share. Of course, our P2P is already here for people who want a comparison tool about price and performance, but this application isn’t able to translate all our knowledge. Then before to create another super visualization tool to expose our data, we thought that laying words on electronic paper would be a good and quick solution. So here’s a first article of a series presenting small and medium size cloud providers that aren’t on all lips but worth it.

The first platform studied in this series called “Out of the wood” is Kamatera, a medium sized vendor with an international offering.

Who are they

Firstly Kamatera should be qualified by their worldwide presence with datacenters in North America, Europe, Middle East and China.  Not only with single locations on continents, but pretty well scattered, covering for instance in the Eastern, Western and Central USA.

Following our methodology we class Kamatera as a medium size provider, they are mainly a cloud compute vendor providing IaaS. But on top of that, they give a major attention to the customer service, then you are free to use their infrastructure with high-level support or benefit from their managed services guaranteed by their teams.

In terms of cloud services, they present all the required features for a decent compute provider:

  • Virtual machines scaling up to 72 CPU and 384GB of RAM
  • VPC management
  • Block storage powered by SSD
  • Load balancer
  • Firewall
  • Multi-user management
  • API

More than IaaS, they also propose a great-sized catalog of SaaS services based on their VMs. Called services and apps, they allow users to opt-in for a preconfigured MongoDB, Rancher or WordPress without extra costs.

How is their platform

Let’s dive into their cloud servers design. Kamatera chose a flexible shaping of virtual machines, meaning that you can set a number of CPU and amount of RAM for each server you launch. 8CPU-8GB or 15CPU-200GB, everything is possible permitting an accurate composition of your infrastructure.

Above that, 4 kinds of VM exist:

  • General Purpose (B) : Dedicated CPU thread
  • Dedicated (D) : Dedicated CPU Core (2 threads)
  • Burstable (T) : Dedicated CPU thread with extra costs after 10% of utilization
  • Availability (A) : Non-dedicated CPU thread with no resources guaranteed

Again, by providing these types of vCPU, Kamatera allows consumers to adjust pricing and performance with their workload. No need to make a choice in a memory-optimized series for your Redis cluster, just design servers fitting your requirements.

Performance insights

We’ve launch our machinery on their infrastructure, collecting hardware specifications and metrics such as Geekbench scores or CPU steal. From our analysis, we are in a VMware ecosystem with Intel processors. Here’s a sample of chips we discovered across their datacenters:

  • Intel Xeon CPU E5-2620 v2
  • Intel Xeon CPU E5-2660 v3
  • Intel Xeon CPU E5-2697A v4
  • Intel Xeon CPU Gold 6150
  • Intel Xeon CPU Platinum 8270

From tests ran by our automated platform Kamatera obtains good a performance set, you’ll find below graphs representing their 2CPU-4GB VMs and different families at Microsoft Azure. We picked all the different type of vCPU available at Kamatera:

Compared to this well-known big player, Kamatera really performs well. This is just a sample and our extensive testing reveal that CPU performance increases almost linearly with the number of vCPU. Moreover, the charts above represent pretty well the 4 kind of vCPU: Dedicated performs the best, then General Purpose, Burstable then Avaibility.

Beyond their honorable performance, another great characteristic of Kamatera is their aggressive pricing. Despite they don’t have long term billing options like 1 or 3 year, their general purposes hourly rates is still lower than the major part of the competitors. Here’s a comparative table with the flavors used above:

Flavor Hourly price Monthly price
2ACPU 4GB 0.022 16.06
2BCPU 4GB 0.053 38.69
2DCPU 4GB 0.088 64.24
2TCPU 4GB 0.022 16.06
Standard_A2_v2 0.076 55.48
Standard_B2s 0.042 30.66
Standard_F2 0.099 72.27
Standard_F2s_v2 0.085 62.05

They also propose a monthly billing at the same price than hourly but 1TB of outgoing traffic are offered with this subscription. With VMs billed hourly Kamatera proposes a worldwide price of $0.01$ / GB which is still up to a tenth the costs announced by big-players.

Portrait of conclusion

Kamatera is a good representative of this market share, very valuable, who offers a worldwide infrastructure at a decent price. They don’t have the plethora of specific services findable on hyperscalers but their pricing and abilities can match with a great part of budgets and workloads.

To get more insight and create you own comparative chart or table, I invite you to go to our Price/Performance Portal,