DigitalOcean is an infrastructure-as-a-service (IaaS) platform from the company of the same name headquartered in New York. It is known for its support of managed Kubernetes clusters and “droplets” feature.
$5
Starting Price Per Month
Cloud BigTable
Score 8.4 out of 10
N/A
Google's Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability.
$0.03
per month per GB
Pricing
DigitalOcean
Google Cloud BigTable
Editions & Modules
1GB-16GB
$5.00
Starting Price Per Month
8GB-160GB
$60.00
Starting Price Per Month
Backup Storage
$0.026
per month per GB
HDD storage
$0.026
per month per GB
SSD storage
$0.17
per month per GB
Nodes
$0.65/hour
per month per node (minimum 1 nodes)
Offerings
Pricing Offerings
DigitalOcean
Cloud BigTable
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
DigitalOcean
Google Cloud BigTable
Features
DigitalOcean
Google Cloud BigTable
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
DigitalOcean
8.3
Ratings
3% above category average
Google Cloud BigTable
-
Ratings
Service-level Agreement (SLA) uptime
9.20 Ratings
00 Ratings
Dynamic scaling
9.00 Ratings
00 Ratings
Elastic load balancing
7.00 Ratings
00 Ratings
Pre-configured templates
10.00 Ratings
00 Ratings
Monitoring tools
10.00 Ratings
00 Ratings
Pre-defined machine images
7.60 Ratings
00 Ratings
Operating system support
8.40 Ratings
00 Ratings
Security controls
9.00 Ratings
00 Ratings
Automation
5.00 Ratings
00 Ratings
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
DigitalOcean is a powerful tool with respect to the services and pricing that it offers. It is easier than other products and also provides servers that are inexpensive with great performance. DigitalOcean also offers additional add-ons such as additional IP addresses, scheduling of backups, etc. One of the best advantages is that it is efficient and is open source. Although, it is suited for a firm that is looking to cut down cost. Also, it is not suited for an organization where the dev/platform/DBA team is less experienced.
Google Bigtable is ONLY suited for massive data sets which scale PetaBytes and TerraBytes. Anything under this can easily be done via dedicated VMs and open source tools. Google Bigtable is expensive and shall be used wisely. It should be utilised only where it is well suited else you would simply be wasting dollars and not utilizing its full benefits.
Ease of use - You can get set up with a new server in a matter of minutes. It doesn't get any easier than that.
Support - The public forums are incredibly helpful as are the official help articles. I've never needed to contact the support team because of this. All of the information is at my fingertips.
Pricing - We're only paying $10/mo for a solution that gives our customers more confidence in us and is a selling point for us.
Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.
Some products/services available on other Cloud providers aren't available, but they seem to be catching up as they add new products like Managed SQL DBs.
While they have FreeBSD droplets (VMs), support for *BSD OSs is limited. I.e. the new monitoring agent only works on Linux.
There are no regions available on South America.
They don't seem to offer enterprise-level products, even basic ones as Windows Server, MS SQL Server, Oracle products, etc.
User interface's responsiveness: I understand so much is going on under the hood, but laggyness is acceptable if a workload is running or being processed. In case their is not workload being process, GUI should work blazing fast. I have faced this at times, and this becomes frustrating as well.
Nothing other than this - BigTable is quite efficient platform and does exactly what it is built for.
With DigitalOcean it is very easy to start up a server/droplet. They have several templates and server images to select from, and they have good instructions on how to get a server set up and started. The monitoring tools in the dashboard look good and are easy to understand.
For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.
They have always been fast, and the process has been straight-forward. I haven't had to use it enough to be frustrated with it, to be honest, and when I have an issue they fix it. As with all support, I wish it felt more human, but they are doing aces.
I chose DigitalOcean over Oracle Cloud because it's simpler, more cost-effective, and quicker to deploy. DigitalOcean’s intuitive interface allows me to manage servers easily, while Oracle Cloud is more complex and suited for larger enterprises. Also, DigitalOcean’s transparent pricing helps control costs, unlike Oracle’s more intricate and complex pricing model.
DigitalOcean has very competitive egress pricing, which has been positive for reducing our costs when running services with a large amounts of data transfer
DigitalOcean templates have helped us quickly launch services that would otherwise require a lot of configuration (saving time)
We haven't had much in the way of negative ROI impacts using DigitalOcean as we don't use it extensively for our core product, but based on personal project experience it can require more engineering time to get up and running with than some other infrastructure services like Heroku. This has been one of the greatest barriers in pushing its adoption in our organization.