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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Data Backup
  5. Amazon Glacier vs Azure Machine Learning

Amazon Glacier vs Azure Machine Learning

OverviewComparisonAlternatives

Overview

Amazon Glacier
Amazon Glacier
Stacks120
Followers97
Votes10
Azure Machine Learning
Azure Machine Learning
Stacks241
Followers373
Votes0

Amazon Glacier vs Azure Machine Learning: What are the differences?

Developers describe Amazon Glacier as "Low-cost storage service that provides secure and durable storage for data archiving and backup". In order to keep costs low, Amazon Glacier is optimized for data that is infrequently accessed and for which retrieval times of several hours are suitable. With Amazon Glacier, customers can reliably store large or small amounts of data for as little as $0.01 per gigabyte per month, a significant savings compared to on-premises solutions. On the other hand, Azure Machine Learning is detailed as "A fully-managed cloud service for predictive analytics". Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

Amazon Glacier and Azure Machine Learning are primarily classified as "Data Backup" and "Machine Learning as a Service" tools respectively.

Some of the features offered by Amazon Glacier are:

  • 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.

On the other hand, Azure Machine Learning provides the following key features:

  • Designed for new and experienced users
  • Proven algorithms from MS Research, Xbox and Bing
  • First class support for the open source language R

According to the StackShare community, Amazon Glacier has a broader approval, being mentioned in 24 company stacks & 9 developers stacks; compared to Azure Machine Learning, which is listed in 12 company stacks and 8 developer stacks.

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Detailed Comparison

Amazon Glacier
Amazon Glacier
Azure Machine Learning
Azure Machine Learning

In order to keep costs low, Amazon Glacier is optimized for data that is infrequently accessed and for which retrieval times of several hours are suitable. With Amazon Glacier, customers can reliably store large or small amounts of data for as little as $0.01 per gigabyte per month, a significant savings compared to on-premises solutions.

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

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.
Designed for new and experienced users;Proven algorithms from MS Research, Xbox and Bing;First class support for the open source language R;Seamless connection to HDInsight for big data solutions;Deploy models to production in minutes;Pay only for what you use. No hardware or software to buy
Statistics
Stacks
120
Stacks
241
Followers
97
Followers
373
Votes
10
Votes
0
Pros & Cons
Pros
  • 6
    Cold Storage
  • 3
    Easy Setup
  • 1
    Cheap
No community feedback yet
Integrations
No integrations available
Microsoft Azure
Microsoft Azure

What are some alternatives to Amazon Glacier, Azure Machine Learning?

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Inferrd

Inferrd

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

GraphLab Create

GraphLab Create

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

AI Video Generator

AI Video Generator

Create AI videos at 60¢ each - 50% cheaper than Veo3, faster than HeyGen. Get 200 free credits, no subscription required. PayPal supported. Start in under 2 minutes.

BigML

BigML

BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.

Vexub

Vexub

Create high-quality videos in seconds with Vexub’s AI generator, turning your text or audio into ready-to-publish content for TikTok, YouTube Shorts, and other short-form platforms

Image to Video AI: Easy AI Image Animator Online

Image to Video AI: Easy AI Image Animator Online

Instantly transform any static image into a dynamic, engaging video with our AI image animator. Create stunning animations, moving photos, and captivating visual stories in seconds. No editing skills required.

SAM 3D

SAM 3D

Explore SAM 3D to reconstruct 3D objects, people and scenes from a single image. Build 3D assets faster with SAM 3D Objects and SAM 3D Body.

Sketch To

Sketch To

Instantly convert images to sketches online for free with our powerful AI sketch generator. Need more power? Upgrade to our Professional model for industry-leading results.

Page d'accueil

Page d'accueil

Thaink² Analytics, la plateforme data et IA de nouvelles génération pour gérer vos projets de bout-en-bout. Fini les pipelines de données instables, les modèles ML/IA qui restent au stade du POC.

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