Haystack vs RAGFlow

Side-by-side comparison of features, pricing, and ratings

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At a glance

DimensionHaystackRAGFlow
PricingFree (open-source), Enterprise: contact salesFree (open-source), Cloud: pay-as-you-go, Enterprise: contact sales
Best forDevelopers building custom RAG and agent pipelinesEnterprises needing high-precision retrieval with visual workflows
Ease of useCode-heavy, requires Python expertiseVisual UI, lower-code, agent sandbox
DeploymentSelf-hosted, Kubernetes-ready, cloud-agnosticSelf-hosted or managed cloud, Docker/K8s
Latest version2.30.2 (Jun 2026)0.26.2 (Jun 2026)
CommunityMature, large community, extensive docsGrowing, focused on enterprise features

Choose Haystack if you are a developer who wants full control over RAG pipelines and agent orchestration with flexibility across LLM providers and deployment environments, and you are comfortable coding. Choose RAGFlow if your team needs an enterprise-oriented, visual RAG platform with strong ETL and built-in connectors for productivity tools, and you prefer less coding.

Haystack
Haystack

Open-source framework for production-ready AI agents and RAG pipelines

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RAGFlow
RAGFlow

Open-source RAG engine for enterprise AI agent context.

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Pricing
Freemium
Freemium
Plans
$0/mo
Custom
Custom
$0/mo
$29/mo ($59/mo after promo)
$129/mo ($259/mo after promo)
Custom
Popularity
5.1k views
5.4k views
Skill Level
Intermediate
Advanced
API Available
Platforms
API
WebAPI
Categories
💻 Code & Development🤖 Automation & Agents
⚙️ Developer Infrastructure
Features
Modular AI framework for building RAG pipelines
Standardized tool calling for AI agents
Hybrid retrieval strategies (dense + sparse)
Serializable, cloud-agnostic pipeline serialization
Kubernetes-ready deployment support
Built-in logging and monitoring
Branching and looping pipelines for complex workflows
Jinja-2 template engine for content generation
Multimodal support for image and audio processing
Context engineering for scalable memory and tool use
Open architecture with no vendor lock-in
Plain string input support for ChatGenerators (2.30+)
Community support via Discord and GitHub
Integration with Gemini Embedding 2 for multimodal search
Open-source RAG engine (Apache 2.0)
Built-in ETL ingestion pipeline for multi-format data
Hybrid search (vector + BM25 + custom scoring + reranking)
Visual AI agent orchestration with MCP integration
GraphRAG with checkpoint-resume (v0.26)
Auto-populated model lists for 11 providers
Incremental data connectors for Outlook, OneDrive, Teams, Slack, SharePoint, Salesforce, Azure Blob
Multi-key per provider support
Deploy assistants to Discord and Feishu (v0.26.1)
Langfuse session traces for multi-turn chats (v0.26.1)
Modify model type for existing configs (v0.26.1)
Agent sandbox for testing workflows (v0.25)
Memory API and user-level memory (v0.24)
Browser component in agent workflows (v0.25.6)
RAPTOR AHC mode stabilization (v0.25.6)
Integrations
OpenAI
Anthropic
Mistral
Hugging Face
Weaviate
Pinecone
Elasticsearch
Gemini Embedding 2
Slack
SharePoint
Salesforce
OneDrive
Outlook
Teams
Azure Blob
Discord
Feishu
Langfuse
GitHub
Ollama
OpenRouter
vLLM
LM-Studio

Feature-by-feature

Haystack is a modular Python framework for building RAG and agent pipelines. It offers standardized tool calling, hybrid retrieval (dense + sparse), branching/looping pipelines, Jinja2 templating, and multimodal support. Its strength lies in full pipeline observability, serializable DAGs, and vendor neutrality. Recent v2.30 allows plain string input to ChatGenerators. RAGFlow is a visual RAG engine with a built-in ETL pipeline for multi-format data (PDFs, images, Office docs). It combines vector search, BM25, and reranking for precision. v0.26.2 adds WhatsApp, DingTalk, WeCom connectors; v0.26.1 adds Discord/Feishu deployment and Langfuse tracing. RAGFlow’s agent sandbox and visual workflow orchestration (including MCP) make it more accessible for teams that want to configure rather than code. Haystack excels in flexibility and debugging; RAGFlow excels in data ingestion and precision retrieval for enterprise documents.

Pricing compared

Both are open-source (Apache 2.0). Haystack offers a free community edition and an Enterprise tier with managed hosting, support, and SSO (contact sales). RAGFlow offers a free self-hosted version and a Cloud version with a free tier (limited queries/storage) and pay-as-you-go scaling, plus Enterprise for on-premise deployments. Haystack’s pricing is typical for an open-source framework where costs come from hosting and any Enterprise subscription. RAGFlow’s cloud model provides a lower-friction entry point for teams wanting managed infrastructure. For large-scale production, both require compute for inference and vector stores. Haystack’s broader integration ecosystem may reduce vendor-specific costs, while RAGFlow’s built-in ETL and connectors could save integration engineering time.

Who should pick which

  • Developer building custom RAG app
    Pick: Haystack

    Haystack offers full code-level control, hybrid search, and flexible pipeline design, ideal for tailoring retrieval to specific data and LLMs.

  • Enterprise team automating document Q&A
    Pick: RAGFlow

    RAGFlow’s strong ETL, visual workflows, and connectors for Office 365/SharePoint streamline ingesting corporate documents with high retrieval accuracy.

  • AI agent builder needing tool calling
    Pick: Haystack

    Haystack’s standardized tool calling and MCP guide provide native agent support, plus branching pipelines for complex decision logic.

  • Non-technical analyst setting up a knowledge base
    Pick: RAGFlow

    RAGFlow’s visual UI and agent sandbox allow configuring retrieval and orchestration without code, reducing reliance on engineering.

Frequently Asked Questions

Can Haystack handle multimodal inputs?

Yes, Haystack supports image and audio processing within its pipelines.

Does RAGFlow support incremental indexing?

Yes, since v0.26 RAGFlow has incremental data connectors for Outlook, OneDrive, Teams, Slack, SharePoint, Salesforce, and Azure Blob.

Is Haystack easy to deploy on Kubernetes?

Yes, Haystack is Kubernetes-ready with serializable pipelines and official Helm charts.

Can RAGFlow deploy assistants to messaging platforms?

Yes, v0.26.1 added deployment to Discord and Feishu, and v0.26.2 added WhatsApp, DingTalk, WeCom.

Which tool has better search accuracy?

RAGFlow emphasizes high-precision retrieval with hybrid search and reranking; Haystack offers hybrid retrieval but relies on user configuration.

Can I use Haystack with any LLM provider?

Yes, Haystack integrates with OpenAI, Anthropic, Mistral, Hugging Face, among others, and is provider-agnostic.

Does RAGFlow have a visual pipeline builder?

Yes, RAGFlow provides a visual drag-and-drop interface for orchestrating AI agents and RAG workflows.

What are the main differences in community support?

Haystack has a larger, more mature community with extensive documentation; RAGFlow's community is smaller but growing quickly, focused on enterprise features.

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