AWS Deep Learning AMIs vs. Ray Comparison


AWS Deep Learning AMIs Amazon	Ray Anyscale	+	+
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About AWS Deep Learning AMIs (DLAMI) provides ML practitioners and researchers with a curated and secure set of frameworks, dependencies, and tools to accelerate deep learning in the cloud. Built for Amazon Linux and Ubuntu, Amazon Machine Images (AMIs) come preconfigured with TensorFlow, PyTorch, Apache MXNet, Chainer, Microsoft Cognitive Toolkit (CNTK), Gluon, Horovod, and Keras, allowing you to quickly deploy and run these frameworks and tools at scale. Develop advanced ML models at scale to develop autonomous vehicle (AV) technology safely by validating models with millions of supported virtual tests. Accelerate the installation and configuration of AWS instances, and speed up experimentation and evaluation with up-to-date frameworks and libraries, including Hugging Face Transformers. Use advanced analytics, ML, and deep learning capabilities to identify trends and make predictions from raw, disparate health data.	About Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Deep Learning solution that helps developers quickly build scalable, secure deep learning applications	Audience ML and AI Engineers, Software Developers
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing Free Open source. Consumption-based. Free Version Supported Free Trial Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Supported
Company Information Amazon Founded: 2006 United States aws.amazon.com/machine-learning/amis/	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives AWS Neuron Amazon Web Services	Alternatives Anyscale
Horovod	Horovod
Google Cloud Deep Learning VM Image Google	Determined AI
Fabric for Deep Learning (FfDL) IBM	Neuralhub
GPUonCLOUD View All	Automaton AI View All
Categories AI Infrastructure Supported AI/ML Model Training Supported Deep Learning Supported	Categories Deep Learning Supported Machine Learning Supported ML Model Deployment Supported

Integrations Amazon EC2 Trn2 Instances Supported Amazon Web Services (AWS) Supported AWS Neuron Supported Amazon EC2 G5 Instances Supported Amazon EC2 P4 Instances Supported Amazon EC2 Trn1 Instances Supported Amazon EKS Not Supported Amazon SageMaker Not Supported Anyscale Not Supported Azure Kubernetes Service (AKS) Not Supported Feast Not Supported Google Cloud Platform Not Supported Google Kubernetes Engine (GKE) Not Supported LanceDB Not Supported MLflow Not Supported PuppyGraph Supported PyTorch Not Supported Python Not Supported Snowflake Not Supported io.net Not Supported Show More Integrations View All 9 Integrations	Integrations Amazon EC2 Trn2 Instances Supported Amazon Web Services (AWS) Supported AWS Neuron Not Supported Amazon EC2 G5 Instances Not Supported Amazon EC2 P4 Instances Not Supported Amazon EC2 Trn1 Instances Not Supported Amazon EKS Supported Amazon SageMaker Supported Anyscale Supported Azure Kubernetes Service (AKS) Supported Feast Supported Google Cloud Platform Supported Google Kubernetes Engine (GKE) Supported LanceDB Supported MLflow Supported PuppyGraph Not Supported PyTorch Supported Python Supported Snowflake Supported io.net Supported Show More Integrations View All 22 Integrations
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