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Application Patterns & Adoption

Reaktor can be adopted in two primary ways: starting a new (greenfield) project or integrating it into an existing (brownfield) system.

Greenfield Application Patterns

The following patterns are easily scaffoldable via the reaktor-cli:

Application TypeReaktor ModulesKey Benefit
Social / CommunityGraph + Auth + DB + Mesh + Actors + UIOffline-first, real-time P2P with graph-based recommendations.
E-CommerceGraph + Auth + DB + Service + WorkersDurable Object inventory coordination and multi-region typed contracts.
EdTech / LearningGraph + Auth + DB + AI Nodes + ActorsKnowledge graphs, AI learning paths, and collaborative study.
IoT DashboardGraph + Mesh + Actors + Telemetry + C++Sensor actors, SIMD signal processing, and edge inference.
Multiplayer GameGraph + Mesh + Actors + C++P2P WebRTC, actor game state, and SIMD physics.
Enterprise ToolGraph + Auth + DB + Service + RN bridgeTyped RPC, RBAC auth, and offline field applications.
AI-Powered SaaSGraph + Auth + AI Nodes + AgentsAgents as graph nodes with caching, fallbacks, and usage tracking.

Brownfield Adoption for Existing Systems

For organizations with mature codebases (e.g., Myntra or Flipkart), a phased adoption strategy is recommended:

  • Months 1-2: Feature Integration: Integrate Reaktor into a single feature. The service layer handles offline caching and typed API contracts while the existing backend remains unchanged.
  • Months 3-4: Introspection: Add telemetry and the Blueprint editor to visualize the system as a live graph, helping convert skeptics within the organization.
  • Months 5-6: Proxying: Use ServiceNode proxies to connect Reaktor to existing backend services. The backend remains untouched, while frontend code begins to leverage Reaktor's benefits.
  • Months 7-12: Full Platform Adoption: Gradually transition to using the Reaktor Mesh for real-time features, Durable Objects for edge caching, and AI agents.

Key Selling Point for Enterprise

Reaktor doesn't replace existing systems; it wraps them in a typed, observable, and deployable graph. For example, Spring Boot services can become graph nodes via ServiceNode proxies, making the entire system visible and composable without throwing away any existing investments.