Open Source · RAG
Quiver
Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama.
Our verdict
We have not reviewed Quiver yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Quiver
Quiver is a Python framework for building retrieval-augmented generation (RAG) systems that abstracts away infrastructure complexity. It supports any LLM (GPT-4, Groq, Llama), any vector store (PGVector, Faiss), and any file type, letting you focus on application logic rather than RAG plumbing.
Best for
Python developers building RAG features into existing applications who want to avoid vendor lock-in and infrastructure boilerplate.
Use cases
- Integrate RAG into existing Python applications without rewriting core logic
- Swap LLMs or vector stores without changing application code
- Build document-grounded chatbots or Q&A systems with minimal boilerplate
Notes
39,173 stars on GitHub. Last updated 2025-07-09.
Pros
- Vendor-agnostic design reduces lock-in and lets you choose best-of-breed components
- Handles file ingestion and vector store operations out of the box
- Active open source project with 39k+ stars and community support
Cons
- Opinionated architecture may not suit teams wanting full control over RAG pipeline design
- Python-only, not suitable for non-Python tech stacks
- Community-maintained project with no commercial support guarantee
Key facts
What we have checked
- Latest prerelease version
- 2.0.0-alpha.7 (released 14 Oct 2026)
- GitHub stars
- 39,554
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How Quiver is growing
39,173 to 39,554
Alternatives
Alternatives to Quiver
| Record | Type | How we know | Checked |
|---|---|---|---|
| TensorSpaceAlternative to this | Open source | Named in the listing | Not dated |
| FlowiseThis is an alternative to it | Open source | Named in the listing | Not dated |
| LangChainThis is an alternative to it | App | Named in the listing | Not dated |
| LangflowThis is an alternative to it | Open source | Named in the listing | Not dated |
| R2RThis is an alternative to it | Open source | Named in the listing | Not dated |
Compare
Compare Quiver side by side
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 2.0.0-alpha.7
Released 2.0.0-alpha.6
Released 2.0.0-alpha.5
Released 2.0.0-alpha.4
Released 2.0.0-alpha.3
Released 2.0.0-alpha.2
Released 2.0.0-alpha.1
Released core-0.0.33
Released core-0.0.32
Released core-0.0.31
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
LangChain
Various
LangChain provides the engineering platform and open source frameworks developers use to build, test, and deploy reliable AI agents.
Flowise
Flowise
Assemble agent and language-model workflows using a visual builder.
Langflow
Community
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
R2R
Community
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Milvus
Community
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Ollama
Ollama
Run supported language models on your computer, with additional cloud options.
Qdrant
Community
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
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