Azure Blobs vs AWS S3

in Azure AWS

Part of my ongoing series comparing AWS and Azure for the services where I’ve used both in production. In this post I’ll be looking at the differences between Azure Blob Storage and Amazon S3 for storing and retrieving files.


  • Azure’s logical structure allows you to manage multiple containers at the same time.
  • AWS allows default documents and with that you can host a static site for pennies per month in S3.
  • Azure Blob can integrate Azure Search to allow searching the content of some documents
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Azure Search for Jekyll

in Azure Jekyll

I added Azure Search to my static site built with Jekyll through the use of Azure Functions. Best part, it’s free*.

This example is for Jekyll, it will work with any static site. The only thing Jekyll specific is the JSON representation of the site, and any static site generator should be able to build that file. I’ve used (Pretzel and PieCrust as well, they are both nice tools, but hosting on GitHub pages has it’s advantages).

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Using Azure Functions to Detect Search Indexer Errors

in Azure

Azure Functions are a light weight way to deploy code. It’s part of the “serverless” craze. While I admit I was suspect of serverless, after just this tiny foray, I can definitely see it’s usefulness.

So here’s my real world example of something simple you can do with Azure Functions. It’s just the tip of the iceberg, but it’s better than a Hello Word.

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AWS Cloudsearch vs Azure Search

in AWS Azure

We recently started moving some of our bits from AWS to Azure. One of the first bits to go was the Search. Below is my comparison of the two.


Azure has the ability to automatically index data stored in SQL, DocumentDB, and Azure Table Storage as well as documents stored in Azure Blob Storage. Azure’s API is strongly typed and much more expressive than AWS’s.

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