Amazon Deep Learning AMIs vs. Iguazio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Deep Learning AMIs
Score 8.7 out of 10
N/A
AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep learning frameworks and interfaces such as TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new…N/A
Iguazio
Score 10.0 out of 10
N/A
Iguazio, headquartered in Herzliya, provides a Data Science Platform to automate machine learning pipelines. It aims to accelerate the development, deployment and management of AI applications at scale, enabling data scientists to focus on delivering better, more accurate and more powerful solutions instead of spending their time on infrastructure. The platform is open and deployable anywhere - multi-cloud, on prem or edge. The vendor states Iguazio powers real-time data science applications for…N/A
Pricing
Amazon Deep Learning AMIsIguazio
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon Deep Learning AMIsIguazio
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
Amazon Deep Learning AMIsIguazio
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Iguazio
9.9
2 Ratings
16% above category average
Connect to Multiple Data Sources00 Ratings10.02 Ratings
Extend Existing Data Sources00 Ratings10.02 Ratings
Automatic Data Format Detection00 Ratings10.02 Ratings
MDM Integration00 Ratings9.52 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Iguazio
9.7
2 Ratings
14% above category average
Visualization00 Ratings9.52 Ratings
Interactive Data Analysis00 Ratings10.02 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Iguazio
9.7
2 Ratings
16% above category average
Interactive Data Cleaning and Enrichment00 Ratings10.02 Ratings
Data Transformations00 Ratings9.52 Ratings
Data Encryption00 Ratings9.52 Ratings
Built-in Processors00 Ratings10.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Iguazio
9.7
2 Ratings
13% above category average
Multiple Model Development Languages and Tools00 Ratings10.02 Ratings
Automated Machine Learning00 Ratings9.52 Ratings
Single platform for multiple model development00 Ratings10.02 Ratings
Self-Service Model Delivery00 Ratings9.52 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Iguazio
9.7
2 Ratings
12% above category average
Flexible Model Publishing Options00 Ratings10.02 Ratings
Security, Governance, and Cost Controls00 Ratings9.52 Ratings
Best Alternatives
Amazon Deep Learning AMIsIguazio
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Posit
Posit
Score 9.1 out of 10
Mathematica
Mathematica
Score 8.2 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon Deep Learning AMIsIguazio
Likelihood to Recommend
10.0
(2 ratings)
10.0
(2 ratings)
User Testimonials
Amazon Deep Learning AMIsIguazio
Likelihood to Recommend
Amazon AWS
Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.
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Iguazio
With Iguazio we are able to scale up our organisations AI infrastructure which us vital to meet business goals and accelerate time-to-time. We are also able to manage our ML pipeline end-to-end using a full-stack,user-friendly environment, feature-rich integrated feature store and powerful data transformation and real-time feature engineering capabilities.
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Pros
Amazon AWS
  • Setting up environment
  • Support for different types of machines
  • Perfect for Machine Learning / Deep Learning use cases
  • Nvidia / Cuda / Conda support easily
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Iguazio
  • Dynamic scaling capacity.
  • Central Metadata management.
  • Data ingestion and preparation.
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Cons
Amazon AWS
  • Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
  • It can be a bit confusing to switch between frameworks for novice users
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Iguazio
  • The user interface is not so much user-friendly, and easy-to-use, navigate.
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Alternatives Considered
Amazon AWS
Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.
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Iguazio
Execution, experiment, data, model tracking, and automated deployment is done automatically through the MLRun serverless runtime engine. MLRun maintains a project hierarchy with strict membership and cross-team collaboration. End-to-end data governance is fully solidified and managed with authentication and identity management. Customers securely share data by providing access directly to it and not to copies.
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Return on Investment
Amazon AWS
  • Saves a lot of Infra Costs
  • Saves a lot of time in handling environment issues
  • Easy to start a new instance
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Iguazio
  • Is a fully integrated solution with a user-friendly portal.
  • Manage our ML pipeline end-to-end using Full-stack,user friendly environment.
  • Iguazio enables our teams to manage all artefacts throughout their lifecycle.
  • Enhance team work and collaboration in our teams.
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