There is no doubt that AWS dominates the cloud market. All this is not because of the Hype, AWS worth to be dominant. The market responded by rewarding AWS with the highest percentage of global business, as it has produced many amazing tools and released great products so far. But that doesn’t mean the AWS will reign the market forever. One more game-changer is running hard and creating cloud products out of all the expertise it used to build a dominant search engine; yes, you are thinking right — Google, it is very competitive and in some respects, can be said better.

Well, sometimes, it makes it hard to say better, as some cloud products are head-and-shoulders above others because the products themselves are usually commodities. A machine that runs the current version of Ubuntu or a cloud storage bucket that stores some gigabytes are interchangeable.

Still, cloud providers are finding ways to go extra mile and stand out in the market by providing additional features. Google Cloud products are starting to create their style, which echoes the powerful simplicity of Google’s consumer-facing products.

Let’s find out the 7 ways Google makes AWS a deal-breaker.

1 — Firebase

Google’s cloud platform offers several different ways to store information, but one of the options, Firebase, is slightly different from the usual repository. Firebase does not store information only. It also replicates data to other copies of the database, including customers, especially mobile clients. In other words, Firebase handles all the push (and pull) from the clients to the servers.

Firebase frees up developers to focus on designing fantastic user experiences. You do not need to manage the servers. You do not need to write APIs. Firebase is your server, your API, and your database, all of which are very generously written and can be customized to suit most of the needs. Yes, you should always use other bits of Google cloud for your advanced applications. Firebase may not be everything to everyone. But it is getting close.

Firebase may look like a database, but in reality, it is a mobile development platform. It has the framework you need to create distributed web or mobile applications. Or mobile web apps for that matter.

2 — BigQuery ML

BigQuery ML is a database, but it’s a machine learning powerhouse. BigQuery ML enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data. (Source: cloud.google.com). There is no need to move data or repack it for some individual machine learning toolkit. These are all in one place, a feature that saves you from having to write a lot of glue code. Then, as an added bonus for SQL jockeys running databases, machine learning is used with an additional keyword in the SQL dialect. You can do the job of an AI scientist with the language of a DBA.

Suggested Read: How Google Cloud SQL is different from other popular databases?

3 — G Guite

G Suite is a set of enterprise-based products, such as Gmail, Drive, Docs, Sheets, etc. Google provides a monthly subscription platform to help you streamline your business. It may seem like a lot of the same Google apps are available for free, but there are some key features that will help your company to integrate with G Suite.

The G Suite for Work provides you with professional email, online storage, shared calendars, video meetings, and more. Google apps make collaboration simple and effective. You’ll have the ability to share spreadsheets and documents, create video conferences with Hangouts, and use instant messaging. You can also share calendars with others by making it easier to schedule meetings.

Ideal for small businesses, G Suite, will provide you with many tools to help you succeed. One advantage is that the G Suite has some great mobile tools. All of the apps are available on mobile phones and tablets, Windows, Mac, or Linux.

4 — Better Virtual CPUs

The Google Compute Engine boosted the maximum power of its instances, putting up to 160 VCUs and 3,844 GB of RAM at your fingertips. When we last looked at the documentation, AWS EC2 instances were exposed to a maximum of 96 vCPUs. Of course, CPUs are not precisely the same power, and they indeed run some streams at different speeds. Adding more virtual CPUs doesn’t always make your software faster. The only real measure is the performance of your problem. But if you want to exult about starting a machine with 160 CPUs, then it’s your chance!

Suggested read: What is Google Compute Engine? How it differs from Azure VM & AWS EC2

5 — Premium Network

Google and Amazon have large networks connecting their data centers, but Google only has a separate “premium” network. This is like a particular fast lane for premium customers, with some reliability and performance guarantees N + 2 redundancy and at least three pathways between data centers. If you want to rely on load balancing on Google CDN and different data centers, choosing a premium network can make life a little bit smoother for your data flows.

Google gives this opportunity to the user to decide by paying more for faster global data movement or to save money and compromise with occasional hiccups.

6 — Preemptible Instance

A preemptible VM is an instance that you can create and run at a much lower price than normal instances. However, Compute Engine might terminate (preempt) these instances if it requires access to those resources for other tasks. Preemptible instances are excess Compute Engine capacity, so their availability varies with usage.

If your apps are fault-tolerant and can withstand possible instance preemptions, then preemptible instances can reduce your Compute Engine costs significantly. For example, batch processing jobs can run on preemptible instances. If some of those instances terminate during processing, the job slows but does not completely stop. Preemptible instances complete your batch processing tasks without placing additional workload on your existing instances and without requiring you to pay full price for additional normal instances. (Source: cloud.google.com)

Last but not the least.

7 — Kubernetes

Kubernetes was developed originally by Google in 2014. It was built upon a decade and a half of the experience that Google has with running production workloads at scale, combined with best-of-breed ideas and practices from the community. It can also facilitate the framework to run distributed systems resiliently.

Read Here: Ok! Google…. What are the Kubernetes best practices?

Kubernetes is a popular open-source platform for the orchestration of containers — that is, management of the applications that are build-out of multiple, large, and self-contained runtimes. According to a survey by Redmonk, Kubernetes usage in Fortune 100 companies’s already at 54%, and with Kubernetes being adopted at such a large scale, it is now de facto standard for container orchestration. This has brought disruptions because it is good news for application developers and software vendors to bring true portability. (Source: Why Kubernetes?)

It is clear that GCP got services, resources and various factors that give them an edge over AWS. But the inability to focus on the growing cloud markets is what put GCP on the backfoot. One such example is the Indian cloud market.

Read here: Why Google Cloud hasn’t picked up in India yet?

To keep up the pace with other Cloud Providers, Google is partnering/acquiring to make its place it the market.

It’s worth mentioning that Amazon is dominant for a reason, and its almost impossible to find an area where AWS can be defeated. In all the above cases, it’s ordinarily conceivable to do something similar to AWS.