LlamaIndex vs Mastra
Detailed side-by-side comparison to help you choose the right tool
LlamaIndex
🔴DeveloperAI agent framework
LlamaIndex is an open-source Python and TypeScript framework for building RAG, document workflows, and AI agents — with LlamaCloud for managed parsing, extraction, and indexing.
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FreeMastra
🔴DeveloperAI Agents
TypeScript-native framework for building AI agents, workflows, and RAG pipelines — from the team behind Gatsby.js.
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FreeFeature Comparison
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LlamaIndex - Pros & Cons
Pros
- ✓Best-in-class retrieval strategies: hybrid, parent-child, summary indexes, knowledge graphs
- ✓LlamaParse is the strongest PDF/document parser for enterprise RAG today
- ✓Open-source library is MIT-licensed and runs anywhere
- ✓Workflows agent layer is a clean alternative to LangGraph for stateful task graphs
- ✓10,000 free LlamaCloud credits make evaluation painless
Cons
- ✗LlamaCloud paid pricing is credit-based and harder to model than seat pricing
- ✗Workflows ecosystem is younger than LangGraph's; fewer multi-agent examples in the wild
- ✗Library API has churned over major releases — older tutorials are often out of date
- ✗Visual builder UX is not part of the product; teams that want no-code go elsewhere
- ✗Pure agent orchestration with complex branching is still cleaner in LangGraph
Mastra - Pros & Cons
Pros
- ✓Best-in-class developer experience — the local playground is genuinely delightful
- ✓Type safety end-to-end via Zod schemas, rare in agent frameworks
- ✓MCP-native in both directions out of the box
- ✓Runs on Cloudflare Workers and Vercel Edge — not Node-only
- ✓Free and open source (MIT) with active backing from a credible founding team
- ✓Avoids the Python context switch for TypeScript-heavy teams
Cons
- ✗Younger ecosystem than CrewAI or LangChain — fewer community integrations
- ✗Mastra Cloud is still in preview with no public pricing yet
- ✗Smaller pool of example crews/templates compared to Python frameworks
- ✗Some advanced RAG features (multi-modal, hybrid search) still in beta
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