Arcade vs Daytona

Detailed side-by-side comparison to help you choose the right tool

Arcade

🔴Developer

AI Infrastructure & Training

An enterprise actions runtime for secure, governed AI-agent access to business systems.

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Starting Price

$0/month
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Daytona

🔴Developer

AI Infrastructure & Training

Open-source sandbox infrastructure for running AI-generated code safely. Sub-90ms startup, per-second billing, and stateful environments for AI agents and code interpreters.

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Starting Price

$0.0504/hr per vCPU
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Feature Comparison

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FeatureArcadeDaytona
CategoryAI Infrastructure & TrainingAI Infrastructure & Training
Pricing Plans3 listed plans4 listed plans
Starting Price$0/month$0.0504/hr per vCPU
Key Features
  • • MCP runtime for secure, reliable production AI agent deployments
  • • Connects identity providers, enforces agent authorization, and enables actions in Google, Slack, and Salesforce
  • • Hobby plan includes 100 user challenges, 1,000 standard tool executions, 50 pro executions, and one hosted MCP server
  • • Sub-90ms Sandbox Creation: Sandboxes boot in under 90 milliseconds, enabling AI agents to request execution environments on demand without noticeable latency. Each sandbox is a fully isolated Linux environment.
  • • Stateful Environments: Unlike ephemeral sandbox providers, Daytona environments persist between sessions. Installed packages, written files, and configured state survive across multiple agent interactions.
  • • MCP Server Integration: Native Model Context Protocol server support allows MCP-compatible AI agents and frameworks to provision, manage, and tear down sandboxes through standardized protocol calls.

Arcade - Pros & Cons

Pros

  • ✓Keeps OAuth tokens and authorization logic outside model context
  • ✓Works across agent frameworks, clients, and model providers
  • ✓Free plan allows a realistic prototype with 2,000 monthly calls
  • ✓Enterprise options cover strict deployment and identity requirements

Cons

  • ✗Adds a security-critical runtime dependency
  • ✗Authentication events and tool calls are billed separately on Team
  • ✗Third-party API changes can still break individual tools
  • ✗Applications still need approvals, idempotency, rollback, and outcome checks

Daytona - Pros & Cons

Pros

  • ✓Sub-90ms sandbox startup is the fastest in the AI code execution space
  • ✓Per-second billing means you pay only for actual compute time, not rounded-up minutes
  • ✓$200 in free credits is generous enough to build and test a full agent workflow before spending anything
  • ✓Stateful environments save time on multi-step agent tasks that need package installation and file persistence
  • ✓Open-source core lets you self-host for full control over data and costs
  • ✓MCP server support simplifies integration with modern AI agent frameworks

Cons

  • ✗GPU pricing ($0.014/second = ~$50/hour) gets expensive fast for sustained ML workloads
  • ✗Newer platform than E2B with a smaller ecosystem of examples and community resources
  • ✗Enterprise and on-premise features require sales engagement with no public pricing
  • ✗Documentation is functional but thinner than established competitors
  • ✗No built-in file upload/download API comparable to E2B's convenience features

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🔒 Security & Compliance Comparison

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Security FeatureArcadeDaytona
SOC2——
GDPR——
HIPAA——
SSO——
Self-Hosted—✅ Yes
On-Prem—✅ Yes
RBAC——
Audit Log——
Open Source—✅ Yes
API Key Auth——
Encryption at Rest——
Encryption in Transit——
Data Residency——
Data Retention——
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Review ArcadeReview Daytona