Google Cloud, Azure, and AWS Differences
October 18, 2016
With so many options for cloud computing, it can be confusing about which one to use for your personal or business files. Three of the most popular cloud computing options are Amazon Web Services (AWS), Google Cloud Platform, and Microsoft Azure. Beyond the pricing, the main differences range from what services they offer and what they name them. Site Point did us a favor with its article comparing the different cloud services: “A Side-By-Side Comparison Of AWS, Google Cloud, And Azure.”
Cloud computing has the great benefit of offering flexible price options, but they can often can very intricate based on how much processing power you need, how many virtual servers you deploy, where they are deployed, etc. AWS, Azure, and Google Cloud do offer canned solutions along with individual ones.
AWS has the most extensive service array, but they are also the most expensive. It is best to decide how you want to use cloud computing because prices will vary based on the usage and each service does have specializations. All three are good for scalable computing on demand, but Google is less flexible in its offering, although it is easier to understand the pricing. Amazon has the most robust storage options.
When it comes to big data:
This requires very specific technologies and programming models, one of which is MapReduce, which was developed by Google, so maybe it isn’t surprising to see Google walking forward in the big data arena by offering an array of products — such as BigQuery (managed data warehouse for large-scale data analytics), Cloud Dataflow (real-time data processing), Cloud Dataproc (managed Spark and Hadoop), Cloud Datalab (large-scale data exploration, analysis, and visualization), Cloud Pub/Sub (messaging and streaming data), and Genomics (for processing up to petabytes of genomic data). Elastic MapReduce (EMR) and HDInsight are Amazon’s and Azure’s take on big data, respectively.
Without getting too much into the nitty gritty, each of the services have their strengths and weaknesses. If one of the canned solutions do not work for you, read the fine print to learn how cloud computing can help your project.