Haystack vs Agno
Side-by-side comparison of two AI agent tools
Short answer
- Agno is growing faster: +560 GitHub stars in the last 30 days vs +318 for Haystack.
- Pick Haystack for: open-source AI orchestration framework for modular RAG pipelines and agent workflows. Pick Agno for: build, run, manage agentic software at scale.
From GitHub data refreshed daily.
Haystackopen-source
Open-source AI orchestration framework for modular RAG pipelines and agent workflows
Agnoopen-source
Build, run, manage agentic software at scale.
Metrics
| Haystack | Agno | |
|---|---|---|
| Stars | 26.6k | 42.5k |
| Star velocity /mo | 317.8421052631579 | 560.0526315789474 |
| Commits (90d) | 768 | 351 |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 539.6K | — |
| Overall score | 0.7901810278193188 | 0.7960554542558297 |
Pros
- +Production-ready architecture with robust testing and type safety (Mypy, comprehensive test coverage)
- +Modular pipeline design allows for flexible composition and customization of AI workflows
- +Strong community adoption with 24,000+ GitHub stars and active development by deepset
- +Production-ready runtime with built-in scalability, session isolation, and native tracing capabilities
- +Comprehensive monitoring and management through AgentOS UI for testing, debugging, and production oversight
- +Simple development experience - build sophisticated agents with memory and tools in approximately 20 lines of Python code
Cons
- -Learning curve may be steep for developers new to AI orchestration frameworks
- -Complexity might be overkill for simple LLM integration use cases
- -Python-focused platform with limited examples for other programming languages
- -Requires multiple dependencies and proper configuration of API keys and database connections
- -May have a learning curve for implementing complex multi-agent workflows and team coordination
Use Cases
- •Building production RAG systems with sophisticated document retrieval and context management
- •Creating AI agent workflows with explicit control over routing and decision-making processes
- •Developing modular AI pipelines that require custom retrieval and context engineering components
- •Building production AI agents with persistent state, memory, and custom tool integrations for customer service or automation
- •Creating multi-agent teams and workflows for complex business processes that require coordination between specialized agents
- •Enterprise deployment of AI agents with comprehensive monitoring, user session management, and production-grade reliability requirements
FAQ
- Which is more popular, Haystack or Agno?
- Agno has more GitHub stars (42,524 vs 26,646).
- Which is more actively developed, Haystack or Agno?
- Haystack had more commits in the last 90 days (768 vs 351).
- Should I use Haystack or Agno?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.