Comparing Anyscale to Open Source Ray
The Anyscale Platform is the best way to run Ray, built by the minds behind Ray. Get started on your existing workloads to Anyscale with no code changes. The result is faster time-to-market and faster iterations across the entire AI lifecycle.
RayTurbo: Anyscale’s Optimized Ray
Ray, Perfected
Ray is the world’s leading AI compute engine. With RayTurbo, unleash the full power of Ray, with improved reliability, efficiency, and fault-tolerance at scale.
Compared to open source Ray, RayTurbo is up to:
- 4.5x faster at running read-intensive data workloads
- 4.5x faster at scaling LLM models like LLaMA-3-70B
- 6.1x cheaper for LLM batch inference (vs AWS Bedrock and OpenAI)
- 90% lower costs through spot instance and elastic training
- 50% fewer nodes through Replica Compaction for better efficiency
- 60% higher QPS serving with optimized Ray Serve
Accelerate Productivity with Integrated Developer Tools
Simplified Developer Environment
Anyscale integrates with VSCode and Jupyter notebook for an integrated IDE experience. Edit and run code, install dependencies, and monitor jobs and resources—just like you would on your laptop.
Automated Dependency Management
Choose how you want to manage dependencies. Use existing base images, bring your own Docker, or use Ray’s runtime environments for faster iteration.
Templates and App Accelerators
Quickstart your AI app creation process with expert-created templates and app accelerators, only available on Anyscale.
Manage Your Resources In a Unified Compute Pool
Unlimited Deployment Options
Choose the deployment option that works best for you. Anyscale supports deployment via a public cloud provider like AWS or GCP, on-prem with Machine Pools, or into your existing Kubernetes cluster. Maintain complete control over your infrastructure.
Hosted Anyscale
Get started instantly by hosting on Anyscale’s cloud. Pay for what you use, without reservations.
Reliable Production Services
Anyscale Jobs
Scale from one node to thousands in 60 seconds or less. Anyscale Jobs is the best way to run your batch workloads in production, with must-have features like Job Queues, automatic retries, and observability features through Ray Dashboard.
Anyscale Services
Deploy your code in moments with Anyscale Services. Seamlessly move from development to production with Replica Compaction, Grafana observability, high availability, zero downtime upgrades, and support for high-volume HTTP traffic.
Best-in-Class Compute Governance
Security and Access Control
All logs and user-related data are securely managed in your private environment. Plus, get auditing and logging for added transparency into user access and actions.
Governance and Compliance
Get user access controls for projects, workspaces, clusters, and cost tracking. Plus, Anyscale has SOC 2 Type II attestation.
Centrally monitor the health of your jobs and resources with out-of-the-box Gradana dashboards. Keep tabs on the costs tied to jobs, clusters, and users in a single intuitive UI.
"What we’re doing would be prohibitively expensive with other AI platforms. Anyscale enables us to quickly take advantage of open models like Llama-3, Mixtral, or whatever comes next, and in AI, there’s always a ‘next’. We’re ready for it with Anyscale."
Deepak Kumar
VP of AI and Data, Handshake
Why Ray Users Choose Anyscale
Faster Time to Market
Develop and ship AI apps faster with Anyscale. See for yourself how customers like Canva report up to 12X faster iteration.
Best Price-Performance
With best-in-class cluster management and scaling support, Anyscale will make sure your applications are always running—without breaking the bank.
Ray Experts
Get access to the minds behind Ray, with options like Ray Training, enterprise-level support, and Professional Services.
FAQs
The best way to experience Anyscale is to book a demo, but you can also explore the platform directly by starting a free trial.
Try Anyscale Today
Build, deploy, and manage scalable AI and Python applications on the leading AI platform. Unlock your AI potential with Anyscale.