---
title: "haystack vs agentic-rag-for-dummies"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/deepset-ai-haystack-vs-giovannipasq-agentic-rag-for-dummies"
tools: ["deepset-ai-haystack", "giovannipasq-agentic-rag-for-dummies"]
---

# haystack vs agentic-rag-for-dummies

*GraphCanon updated Aug 14, 2026*

## Verdict

Pick haystack if haystack is an open-source AI orchestration framework for building context-engineered LLM applications; pick agentic-rag-for-dummies if agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models.

[haystack](https://haystack.deepset.ai) reports 26k GitHub stars, 3.0k forks, and 108 open issues, last pushed Aug 1, 2026. [agentic-rag-for-dummies](https://github.com/GiovanniPasq/agentic-rag-for-dummies) has 3.9k stars, 499 forks, and 0 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [haystack's repository](https://github.com/deepset-ai/haystack) and [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies).

| | [haystack](/tools/deepset-ai-haystack.md) | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) |
| --- | --- | --- |
| Tagline | Open-source AI orchestration framework for building context-engineered LLM applications. | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents |
| Stars | 26,073 | 3,893 |
| Forks | 2,972 | 499 |
| Open issues | 108 | 0 |
| Language | Python | Jupyter Notebook |
| Adopt for | Haystack is an open-source AI orchestration framework for building context-engineered LLM applications. | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | MIT |
| Categories | AI Agents, Data & Retrieval, LLM Frameworks | AI Agents, Data & Retrieval |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [haystack](/tools/deepset-ai-haystack.md) | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Active (82%) |
| Days since push | 0d | 19d |
| Open issues (now) | 108 | 0 |
| Owner type | Organization | User |
| Full report | [trust report](/tools/deepset-ai-haystack/trust.md) | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) |

## Shared compatibility

- **Python**: [haystack](/tools/deepset-ai-haystack.md) - Python runtime; [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) - Python runtime

## Decision facts: haystack

- **Pricing:** freemium - Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources.
- **Requirements:** Min 4 GB RAM; Requires Docker
- **Adopt for:** Haystack is an open-source AI orchestration framework for building context-engineered LLM applications.
- **License detail:** Apache-2.0

## Decision facts: agentic-rag-for-dummies

- **Adopt for:** Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models.

## Choose when

### Choose haystack if…

- haystack is primarily Python; agentic-rag-for-dummies is Jupyter Notebook.
- License: haystack is Apache-2.0, agentic-rag-for-dummies is MIT.
- Pricing: Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources..
- Requirements: Min 4 GB RAM; Requires Docker.
- Tags unique to haystack: agents, ai, gemini, generative-ai.
- Also covers LLM Frameworks.
- You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines.

### Choose agentic-rag-for-dummies if…

- agentic-rag-for-dummies is primarily Jupyter Notebook; haystack is Python.
- License: agentic-rag-for-dummies is MIT, haystack is Apache-2.0.
- Tags unique to agentic-rag-for-dummies: agentic-ai, bm25, gradio, langchain.
- When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph.

## When NOT to use haystack

- You require integration with specific proprietary tools or frameworks not supported by Haystack.
- Your development team is not familiar with Python-based technologies, since Haystack primarily supports Python-based workflows.
- You are looking for a completely managed service rather than an open-source framework that requires more hands-on configuration and customization.

## When NOT to use agentic-rag-for-dummies

- If smaller language model sizes are required as they might ignore retrieval instructions or hallucinate details.
- Projects sensitive about Docker and system requirements must carefully review the outlined conditions for deployment.

## Common questions

### What is the difference between haystack and agentic-rag-for-dummies?

haystack: Open-source AI orchestration framework for building context-engineered LLM applications.. agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. See the comparison table for live GitHub stats and shared categories.

### When should I choose haystack over agentic-rag-for-dummies?

Choose haystack over agentic-rag-for-dummies when haystack is primarily Python; agentic-rag-for-dummies is Jupyter Notebook; License: haystack is Apache-2.0, agentic-rag-for-dummies is MIT; Pricing: Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources.; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to haystack: agents, ai, gemini, generative-ai; Also covers LLM Frameworks; You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines.

### When should I choose agentic-rag-for-dummies over haystack?

Choose agentic-rag-for-dummies over haystack when agentic-rag-for-dummies is primarily Jupyter Notebook; haystack is Python; License: agentic-rag-for-dummies is MIT, haystack is Apache-2.0; Tags unique to agentic-rag-for-dummies: agentic-ai, bm25, gradio, langchain; When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph.

### When should I avoid haystack?

You require integration with specific proprietary tools or frameworks not supported by Haystack. Your development team is not familiar with Python-based technologies, since Haystack primarily supports Python-based workflows. You are looking for a completely managed service rather than an open-source framework that requires more hands-on configuration and customization.

### When should I avoid agentic-rag-for-dummies?

If smaller language model sizes are required as they might ignore retrieval instructions or hallucinate details. Projects sensitive about Docker and system requirements must carefully review the outlined conditions for deployment.

### Is haystack or agentic-rag-for-dummies more popular on GitHub?

haystack has more GitHub stars (26,073 vs 3,893). Stars measure visibility, not whether either tool fits your constraints.

### Are haystack and agentic-rag-for-dummies open source?

Yes - both are open-source projects on GitHub (haystack: Apache-2.0, agentic-rag-for-dummies: MIT).

### Where can I find alternatives to haystack or agentic-rag-for-dummies?

GraphCanon lists graph-backed alternatives at [haystack alternatives](/tools/deepset-ai-haystack/alternatives) and [agentic-rag-for-dummies alternatives](/tools/giovannipasq-agentic-rag-for-dummies/alternatives) ([haystack markdown twin](/tools/deepset-ai-haystack/alternatives.md), [agentic-rag-for-dummies markdown twin](/tools/giovannipasq-agentic-rag-for-dummies/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/deepset-ai-haystack-vs-giovannipasq-agentic-rag-for-dummies.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, haystack or agentic-rag-for-dummies?

haystack: Very active. agentic-rag-for-dummies: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for haystack and agentic-rag-for-dummies?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [haystack trust report](/tools/deepset-ai-haystack/trust); [agentic-rag-for-dummies trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=deepset-ai-haystack`](/api/graphcanon/graph?tool=deepset-ai-haystack)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_