Mastra vs Rasa
Side-by-side comparison to help you choose the best tool.
Mastra
freeMastra is an open-source TypeScript AI system for building agents, workflows, and RAG applications. It provides a unified abstraction for LLM calls, tool use, memory, and workflow orchestration with built-in evaluation and observability. Mastra is designed as a production-ready system with a developer experience comparable to Next.js for AI application development.
Rasa
freemiumRasa is an open-source conversational AI system for building contextual AI assistants and chatbots with full control over data and on-premise deployment. It uses machine learning to understand user intent and manage multi-turn conversations, making it ideal for privacy-sensitive industries. Rasa Pro offers enterprise features including analytics, low-latency inference, and dedicated support for large-scale deployments.
| Feature | Mastra | Rasa |
|---|---|---|
| Pricing | free | freemium |
| Category | - | - |
| Rating | 4.3 | 4.2 |
| Best For | TypeScript developers building production AI agents, workflows, and RAG applications who want a modern, opinionated system with excellent DX | Enterprise teams needing full data control and custom NLU models |
| Views | 4 | 5 |
Pros
- TypeScript-first for frontend and full-stack teams
- Production-ready with built-in evaluation
- Developer experience comparable to Next.js
Cons
- TypeScript only
- Newer framework with smaller community
Pros
- Complete data sovereignty with on-premise hosting
- Highly customisable ML pipeline
- Large open-source community and documentation
Cons
- Significant ML and Python expertise required
- Complex setup compared to no-code alternatives
- TypeScript AI agent framework
- Workflow orchestration
- RAG with built-in vector search
- Built-in evaluation
- Model-agnostic
- Open-source NLU and dialogue management
- Full on-premise deployment capability
- Custom ML model training
- Multi-turn contextual conversations
- REST, Slack, Teams, and custom channel connectors