Analytics on GCP vs AZURE vs AWS

Analytics is the heart of all enterprise apps’ growth and development. If the data collected through the cloud is not collected and interpreted in a proper manner, it can hurt the marketing strategies. This data can be used to develop new products, create updates, predict market trends, and figure out the user demographics.

Let's take a dig into the World’s three mammoth Cloud Providers who turn data into actionable insights- GCP, Azure & AWS.

Most commonly used cloud services include –

• Compute

• Storage

• Database

• Networking and Content Delivery

• Management tools

• Development Tools

• Security

Google Cloud is the next most promising cloud player and is gaining the ground fast over Amazon AWS and Microsoft Azure. However, Amazon Web Services (AWS) has more market share in Cloud Market but Google is penetrating into the market very fast and compete with the existing leaders and when the time is ripe it may become the leader itself.

GCP offers GCE (Google Compute Engine) which handles all the compute services, AWS offers EC2(Elastic Compute Cloud) to do essentially the same thing & Microsoft Azure provides Virtual Machines and Virtual Machine Scale Sets.

The biggest challenge for processing a large amount of data is remission and expenditure. Google’s BigQuery gains its arduous acclaim by analyzing gigabytes to petabytes of data using ANSI SQL at an astounding fast speed and provides REST-based APIs for easy integration with other applications. Cloud Dataflow enables faster streaming and batch data pipeline development without compromising durability, accuracy, or functionality. While AWS has ‘Kinesis’, Azure has ‘Event Hubs,’ both displaying enough firepower for data analysis economically and in situations with low remission.

Cloud platforms need an affordable way to process vast amounts of data they are storing. Here, Amazon has a better storage solution, but they are expensive. The price structure can be complicated and many companies face difficulties in managing their costs.

GCP offers a faster time to value with its open architecture and easy integration with popular open-source tools. Google’s two decades of innovation in machine learning and AI gives it an upper hand where one can bring predictive analytics into their applications using industry-leading services. Azure & AWS have simplistic Machine Learning abilities on their Cloud Platforms.

But the actual research while choosing the best cloud service provider depends on what you need and what the provider offers. So, a good analysis is required while making the selection for the best cloud service provider. So, the first step an entrepreneur should make is to meet his own expectations. When it’s done, the market would be ready for negotiations.