Jeffrey Hicks

Platform Eng @R360

Jido vs Mastra: Framework Comparison

Perplexity research exploring the differences between Jido (Elixir) and Mastra (TypeScript) AI agent frameworks, comparing maturity, features, and production readiness

By Agent Hicks • Aug 24, 2025 • perplexity-export

Maturity & Production Readiness

Jido (Elixir)

Status: Early stage, Version 1.0.0 recently released
Ecosystem: Minimal, requires separate jido_ai package for LLM integration
Production Use: Claims production-ready but limited real-world adoption examples
Community: Small, primarily Elixir-focused community

Mastra (TypeScript)

Status: Mature, viral adoption (1.5K → 7.5K GitHub stars in weeks)
Ecosystem: Comprehensive, built on Vercel AI SDK
Production Use: Used by Fireworks AI, multiple YC companies
Community: Large, growing rapidly with strong backing

Core Features Comparison

Feature	Jido (Elixir)	Mastra (TypeScript)
Agent Definition	Compile-time agents with state schemas	Runtime agents with TypeScript types
Concurrency	BEAM actor model, 10K+ agents	Node.js event loop, standard JS concurrency
Memory Management	Process-based state, 25KB per agent	Persistent memory with vector search
Tool Integration	Custom Actions system	Built-in tools + MCP server support
Workflows	Signal-based message passing	Graph-based workflow engine
AI Integration	Separate `jido_ai` package, basic	Native AI SDK integration, comprehensive
RAG Support	Not built-in	Full RAG pipeline with vector stores
Development Tools	Basic CLI, limited playground	Rich playground with tracing
Deployment	GenServer supervision trees	Serverless, edge, or self-hosted

AI-Specific Capabilities

Jido AI Limitations:

Basic LLM integration through instructor_ex
No native RAG or vector database support
Limited tool calling abstractions
Manual memory management required
Minimal prompt management features

Mastra AI Strengths:

Multi-provider LLM routing (OpenAI, Anthropic, Google)
Built-in RAG pipeline with chunking, embedding, querying
Advanced memory systems with semantic similarity
Rich tool ecosystem including MCP servers
Comprehensive evals and observability
Voice capabilities (TTS, STT)

Development Experience

Jido Code Example:

defmodule WeatherAgent do
  use Jido.Agent, name: "weather_agent"
  
  def start_link(_opts \\ []) do
    Jido.AI.Agent.start_link(
      agent: __MODULE__,
      ai: [
        model: {:openai, model: "gpt-4o-mini"},
        tools: [Jido.Tools.Weather]
      ]
    )
  end
end

Mastra Code Example:

import { Agent } from '@mastra/core';
import { openai } from '@ai-sdk/openai';

const weatherAgent = new Agent({
  name: 'Weather Agent',
  instructions: 'You are a helpful weather assistant',
  model: openai('gpt-4o'),
  tools: {
    getWeather: {
      description: 'Get weather for a city',
      parameters: z.object({ city: z.string() }),
      execute: async ({ city }) => await fetchWeather(city)
    }
  }
});

Ecosystem & Tooling

Jido Ecosystem:

Limited tooling - basic CLI and testing
Small package ecosystem
Requires external services for most AI functionality
Manual integration with vector databases, monitoring
Learning curve requires Elixir/OTP knowledge

Mastra Ecosystem:

Rich development environment with local playground
Extensive integrations (Pinecone, pgvector, Redis)
Built-in observability and tracing
Templates and examples for common patterns
Familiar to JavaScript developers

Performance & Scalability

Jido Advantages:

Extreme concurrency: 10,000+ agents per container
Tiny memory footprint: 25KB per agent
Built-in fault tolerance with supervision trees
Distributed by design across BEAM nodes

Mastra Advantages:

Faster time-to-market with comprehensive features
Better AI capabilities out of the box
Serverless-friendly deployment model
Rich developer tooling accelerates development

When to Choose Each

Choose Jido if:

You’re building massive-scale agent systems (10K+ concurrent agents)
Extreme fault tolerance is critical
Your team has strong Elixir expertise
You need custom AI integration and have time to build tooling
Memory efficiency is paramount

Choose Mastra if:

You want comprehensive AI features out of the box
Rapid development and time-to-market matter
Your team knows TypeScript/JavaScript
You need RAG, memory, and tool integration immediately
You prefer rich development tooling and observability

Bottom Line Recommendation

For AI agent development, Mastra is currently the better choice because:

Feature completeness: RAG, memory, tools, evals built-in
Mature ecosystem: Proven in production, active community
Developer experience: Rich tooling, playground, documentation
AI-first design: Built specifically for modern AI applications

Jido shows promise but is too early-stage for most production AI use cases. Its concurrency advantages are compelling, but the AI tooling gap is significant compared to mature TypeScript frameworks.

Unless you specifically need Elixir’s concurrency model or have existing Elixir infrastructure, Mastra provides a more complete, production-ready solution for building AI agents.