What is Amazon Glacier?
Who uses Amazon Glacier?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon Glacier in their tech stack.
I'm starting to plan a new web app for the company that I'm currently working for. The idea is to create a web app where the user will do all the basic operations (upload, delete, update, etc.) on Amazon Glacier. Users basically will admin the account of AWS Glacier, create vaults, tags, upload files, delete files, etc.. all the options AWS Glacier has to offer.
There will be several users, each user with different AWS Glacier accounts and with unique AWS configurations.
Another important aspect is the security of the information of each user (the AWS Glacier credentials). I believe I'll need to encrypt this information of each user somehow.
I'm having second thoughts if I should develop this project with Django or .NET. What do you think? Or maybe is there a third option I should consider besides Django and .Net?
Amazon Glacier's Features
- Low cost – Amazon Glacier is an extremely low-cost, pay-as-you-go storage service that can cost as little as $0.01 per gigabyte per month.
- You store data in Amazon Glacier as archives. An archive can represent a single file or you may choose to combine several files to be uploaded as a single archive. Retrieving archives from Amazon Glacier requires the initiation of a job. Jobs typically complete in 3 to 5 hours. You organize your archives in vaults.
- Secure – Amazon Glacier supports secure transfer of your data over Secure Sockets Layer (SSL) and automatically stores data encrypted at rest using Advanced Encryption Standard (AES) 256, a secure symmetric-key encryption standard using 256-bit encryption keys.
- Durable – Amazon Glacier is designed to provide average annual durability of 99.999999999% for an archive. The service redundantly stores data in multiple facilities and on multiple devices within each facility.
- Simple – Amazon Glacier allows you to offload the administrative burdens of operating and scaling archival storage to AWS, and makes retaining data for long periods, whether measured in years or decades, especially simple.