Comparison

Canopy vs Ragas

No leader: the top candidate Ragas has only 0.32 confidence (low), below the 0.35 needed to declare a winner. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.

Machine formatsMarkdownJSONGraphQLMarkdown is open. JSON and GraphQL need a free key.
Canopy45
Ragas54
Score
vioscaleAI score
Canopy45 / 100high · 76%
Ragas54 / 100low · 32%
Pricing
Free tier
Canopy✓
Ragas✓
Model
Price level
Canopyfree
Ragasfree
Starting price
Canopy$0.07
Ragas–
Transparent
Canopy✗
Ragas✓
Integrations
Count
Canopy24
Ragas3
Adoption
Dependent repos
Canopy0
Ragas1
Github stars
Canopy1,034
Ragas15,838
Activity
Commits last 30d
Canopy0
Ragas–
Release
Cadence days
Canopy3
Ragas7
History
Canopy13 items
License
Spdx
Language
Primary
CanopyPython
RagasPython
Market
Content
Faq
Canopy6 items
Ragas6 items

Capabilities

Feature-by-feature on the axes that matter for rag tools. “-” means undocumented, not absent.

Capabilities
Hybrid retrieval
Canopy✓
Ragas-
Reranking integration
Canopy✓
Ragas-
Multi hop agentic retrieval
Canopy-
Ragas-
Embedding provider agnostic
Canopy✓
Ragas-
LLM provider agnostic
Canopy✓
Ragas-
Built in rag eval metrics
Canopy✓
Ragas✓
Citation attribution
Canopy✓
Ragas-
Multimodal rag
Canopy-
Ragas-
Managed ingestion pipeline
Canopy✓
Ragas-
Open source
Canopy✓
Ragas✓

What each one is

The product in its own terms, so the numbers below have context.

Canopy

Canopy is an open-source framework that simplifies building RAG applications by handling chunking, embedding, vector storage, chat history, and context retrieval. It provides a CLI tool to interactively evaluate your RAG workflows against non-RAG responses.

Independently observed

Ragas

A Python-based framework that evaluates RAG applications through automatic metrics covering faithfulness, relevance, and recall. Includes tools to synthetically generate test datasets customized for specific use cases, enabling developers to assess LLM application performance at both component and end-to-end levels.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Canopy

from $0.07/GBHybridFree tier

Free tier available. Usage-based Codespaces pricing starting at $0.18/hour compute and $0.07/GB storage. Enterprise plans available.

  • FreeFree
    • Public repositories
    • 2000 CI/CD minutes per month
    • Pull request collaboration
    • Project wiki
    • Dependabot vulnerability alerts
  • Codespaces$0.18 per hour + $0.07 per GB
  • Enterprise CloudContact sales
as of verify ↗

Ragas

Open sourceFree tier
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
CLI
Canopy✓
Ragas✓
Deployment
Cloud / SaaS
Canopy✓
Ragas✗
Self-hosted
Canopy✓
Ragas✓

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

In common (1)
  • OpenAI

Canopy

34 total - 33 not shared
  • Pinecone
  • Qdrant
  • OctoAI
  • Cohere
  • Anyscale
  • Azure OpenAI
  • Google Cloud Run
  • CircleCI
  • Azure Pipelines
  • Codemagic
  • Render
  • CodeRabbit
  • Linear
  • PullRequest
  • Zenhub
  • Zube
  • Codecov
  • Codacy
  • CodeFactor
  • DeepScan
  • GuardRails
  • Coveralls
  • Rollbar
  • Mergify
  • +9 more
Independently observed

Ragas

3 total - 2 not shared
  • LlamaIndex
  • LangSmith
Independently observed
Still deciding?

Canopy or Ragas: which one depends on you

A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.

Free to run, no account needed to start. How the evaluation works

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.