Comparison of Big Data services from Azure, AWS and GCP

I have been searching for the last few days a website that compares the different Big Data and Analytic services for the main cloud providers ( Azure, AWS and Google), and I have not yet been able to find such web page. For this reason, I decided to create this blog.

I am presenting below a comparison table in which I have separated the different phases of a big data analysis process: Data Ingestion, Real-time processing, Batch Processing, Data Access and Long Term Storage.

Each cloud provider set different names for its managed services (PaaS), that's why I'm comparing these services with the corresponding "un-managed" version (IaaS) that can be configured on the cloud or on-premises.

I'm only classifying services and putting them side to side for each cloud provider. I am not trying to compare pros and cons or come up with a winner. That's definitely a theme for another blog.

Important note: As you can see on the table, I am NOT mentioning Hadoop MapReduce or Hive, the reason is that I am a true believer that these technologies are part of the past and that Apache Spark (or maybe Flink) represents the new generation of big data processing.

Enjoy!!