Since the Cloud Computing has become popular over time, I have received quite a lot of questions in my inbox regarding the guideline for choosing a cloud hosting/platform. I hope most of you will find your answers here after reading this comparison.

Apparently, all the cloud hosting services out there are actually expensive if we compare the computing power with a dedicated server. However, it’s still a good move to use cloud hosting if you are ready to scale in the near future or handling unexpected traffic spike.

Overview

Obviously, Amazon AWS is already in the game of cloud since 2006. Google and Microsoft Azure come after 2010 but keep in mind that Older doesn’t mean better. Amazon AWS is current having the highest price compare with Google Cloud. (For choosing similar server, OS and specification)

Compute Power

Overall, AWS is the clear winner but make sure you have a deep pocket if you need the biggest instance.

Storage and Content Delivery

Overall, AWS and Azure are clearly win in terms of storage and content delivery.

AWS and Google’s support for automatic versioning is a great feature that is currently missing from Azure.

If you use the common programming patterns for atomic updates and consistency, such as etags and the if-match family of headers, then you should be aware that AWS does not support them, though Google and Azure do

WARNING: Storage has never been cheaper with headline storage costs looking ridiculously cheep, but pricing can quickly get complicated and unpredictable especially if you plan to move large volumes of data. For object storage all three providers charge per GB of data stored plus a request charge (depending on the nature of the request) plus an egress charge per GB. Storage and egress charges will vary depending on the amount of data involved.

Database

All three providers boast impressive relational, no-sql and petabyte scale data warehouse offerings. RDS supports an impressive range of managed relational stores while Azure SQL Database is probably the most advanced managed relational database available today. Google has limited range of database images.

Analytic and Big Data

AWS certainly has all the bases covered with a solid set of products that will meet most needs. Minor omissions include pre-trained machine learning models and managed lab notebooks but otherwise AWS scores highly across the board.

Azure offers a comprehensive and impressive suite of managed analytical products. They support open source big data solutions alongside new serverless analytical products such as Data Lake. Azure is very strong in the machine learning space, offering pre-trained models through to custom R models running over big data, and is the only provider to offer the capability for organisations to track and document their data assets.

Google provide their own twist to cloud analytics with their range of services. With Dataproc and Dataflow, Google have a strong core to their proposition. Tensorflow has been getting a lot of attention recently and there will be many who will be keen to see Machine Learning come out of preview. Google has a strong rich set of pre-trained APIs but lacks BI dashboards and visualisations.

Application Services

AWS and Azure have a more coherent message with their products clearly integrated into their respective platforms, whereas Google Firebase feels like a distinctly separate product.

Conclusion

After comparing the three cloud platforms in terms of maturity, flexibility, cost effecttiveness and scalability AWS Still the winner after all. It takes time to learn about how to best use AWS, and many times requires organizations to pay for experts to help them, either from AWS or a third-party consultancy. Fortunatetly, AWS has great consultation service and it’s always available when you need to implement large scale web application. AWS is constantly innovating, which is a good for the industry, but it’s difficult for customers to keep up with all the changes sometime. Despite all these challenges, AWS has emerged as the “safe choice” for using the cloud, Gartner says.

Unlike AWS, Azure does not use the concept of Availability Zones even though Azure is available over 36 regions . While Microsoft has a broad and growing international data center footprint, backing up workloads across regions is slightly more difficult in Azure versus AWS.

It’s also more difficult to find experts, consultants and third-party platforms that run on Azure. In the latest Gartner IaaS Magic Quadrant, the research firm called Azure “good enough” for most enterprise workloads.

Google has the longest way to go among the three providers in terms of reaching out and interacting with enterprise clients. This is Microsoft’s strength, and it’s taken AWS almost a decade to build relationships and convince enterprises that it is a trusted partner.