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Layers / Data / RAG / Retrieval and search

Retrieval and search

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The search layer a question actually goes through: hybrid search, reranking, query planning and the plumbing around a corpus. A store that holds the vectors is a vector database; several products are honestly both and are filed in both.

52 in this category
SORTED BY STARS · 3 UNMEASURED, GROUPED LAST

NARROW BY WHAT THIS CATEGORY ASKS

LICENCE · 12 NOT READ

OPEN SOURCE · 27 NOT READ

DEPLOYMENT · 33 NOT READ

PRODUCTUSED BYSTARSDOWNLOADS 30D
ragflowRAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs90,545ElasticsearchPython client for Elasticsearch1177,9019,969,207headroomCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.73,396pathwayPython ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.62,295meilisearchA lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.59,271lightrag[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation39,583quivrOpiniated 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. Any Vectorstore:39,509langchain-chatchatLangchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Ll38,632khojYour AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM into your personal, autonomous AI 37,279pageindex📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG35,622QdrantClient library for the Qdrant vector search engine2234,4862,854,348graphitiBuild Real-Time Knowledge Graphs for AI Agents30,825fastgptFastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letti29,710ChromaA JavaScript interface for chroma1729,270995,418weknoraOpen-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.28,447kotaemonAn open-source RAG-based tool for chatting with your documents.25,745Jina AIMultimodal AI services & pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc.121,860memvidMemory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.16,551OpenMetadataThe Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.15,177Eeasy-datasetA powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval14,902OpenSearchPython client for OpenSearch1213,699txtaiAll-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows12,94317,949SemanticaGraph-Native Infrastructure for Context and Accountable AI Systems12,716claude-contextCode search MCP for Claude Code. Make entire codebase the context for any coding agent.12,515flagembeddingRetrieval and Retrieval-augmented LLMs12,180LanceDBLanceDB: A serverless, low-latency vector database for AI applications1411,3957,286,011orama🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.10,557paradedbOne Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.9,297deeplakeDeeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.9,242deep-searcherOpen Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.8,260VespaPython API for vespa.ai7,0797,243,060redisearchA query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.6,237helix-dbHelixDB is an OLTP graph database with native vector and full-text search built in Rust on Object Storage.5,899autoragAutoRAG: Now your agent can find anything in your computer. It gets smarter if you are using it frequently.5,067MarqoAI-native ecommerce search platform with semantic search and personalization for fashion, beauty, electronics, and home goods.15,032infinityThe AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.4,706ruvectorRuVector is a High Performance, Real-Time, Self-Learning Ai, Vector GNN, Memory DB built in Rust.4,494ruby_llmOne delightful Ruby framework for every major AI provider. Build AI agents, chatbots, RAG apps, and multimodal workflows in beautiful, expressive code.4,357MTEBMTEB: State-of-the-art evaluation of embeddings across languages and modalities3,420socraticodeEnterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-fl3,294knowhereKnowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.3,175yu-ai-agent编程导航 AI 开发实战新项目，基于 Spring Boot 3 + Java 21 + Spring AI 构建 AI 恋爱大师应用和 ReAct 模式自主规划智能体YuManus，覆盖 AI 大模型接入、Spring AI 核心特性、Prompt 工程和优化、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、AI Agent 开发（Manas Java 2,665XxerjXERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command indexes code, docs, logs and PDFs for search2,525agentsetThe open-source RAG platform: built-in citations, deep research, 22+ file formats, partitions, MCP server, and more.2,082GgrepaiSemantic Search & Call Graphs for AI Agents (100% Local)1,860GgptdiscordA robust, all-in-one GPT interface for Discord. ChatGPT-style conversations, image generation, AI-moderation, custom indexes/knowledgebase, youtube summarizer, and more!1,853RagbitsBuilding blocks for rapid development of GenAI applications 1,668synthadocSynthadoc: An open-source LLM knowledge compilation engine that turns raw documents into structured, local-first wikis. A transparent, human-readable alternative to traditional RAG, which can be self-1,176Hhaiku.ragAgentic RAG for local and self-hosted document search: hybrid retrieval, reranking and multimodal RAG on embedded LanceDB, with Docling parsing and an MCP server606Turbopufferfast search engine built on object storageVectaraThe Enterprise Agent PlatformVoyage AIEmbedding models and rerankers for retrieval83,800,718

SORTED BY ONE STATED COLUMN · USED BY = LISTED PRODUCTS DEPENDING ON IT, IN THIS DIRECTORY — NOT A POPULARITY FIGURE · NO OVERALL SCORE AND NO RANK COLUMN, BECAUSE BLENDING ADOPTION, STARS AND DOWNLOADS NEEDS WEIGHTS, AND WEIGHTS ARE AN OPINION PRESENTED AS ARITHMETIC

Cite this page

The count and its date sit inside the citation, because “Retrieval and search” without a date is a claim that quietly goes wrong as the category fills.

infratoapp, “Retrieval and search — Data / RAG”, read 28 October 2026. 52 listed products. https://www.infratoapp.com/layers/data-rag/retrieval

No overall score, and no rank column

Blending adoption, stars and downloads needs weights, and weights are an opinion presented as arithmetic — so this table sorts by one stated column at a time and shows which. This view holds no billing column and joins no billing table: a sponsor cannot appear higher, and the signals meter is a row’s own confidence, never a score you can sort on.

Frequently asked

What is in the Retrieval and search category?
52 products in the Data / RAG layer of the AI stack. The search layer a question actually goes through: hybrid search, reranking, query planning and the plumbing around a corpus. A store that holds the vectors is a vector database; several products are honestly both and are filed in both. Listed members include ragflow, Elasticsearch and headroom. Every fact on each listing carries the page it was read from and the date it was read.
How are Retrieval and search compared here?
By the 7 attributes this category declares, asked of every member and answered only where a source states it. A product with no answer on record shows a gap rather than a guess, and no blended score is published — weights would be an opinion presented as arithmetic.
ragflow or Elasticsearch?
Both are listed under Retrieval and search. We publish no verdict between them — we hold no benchmark that would support one. What we do hold is the same attribute sheet for each, side by side with the source behind every value, at /compare/elasticsearch-vs-ragflow.
What does a blank mean on a retrieval and search row?
That nobody has told us, not that the answer is no. A hollow ring is "no answer on record", which is a different state from a recorded no — and the two look different on purpose. A listing with a blank has not failed the question; it has not been read for it.
How often are retrieval and search figures re-read?
Every value carries the date it was read and a link to the page it came from. Prices move fastest and are re-read most often; an attribute read weeks ago says so rather than presenting itself as current. Anything past 21 days is hidden rather than shown stale.
Is this every retrieval and search there is?
No. This is 52 we have read and can cite. A directory that claimed completeness would be making a promise it cannot keep, so the page states its own count instead and says when a category is too thin to shortlist from.
Can a vendor pay to rank higher here?
No. Nothing on this page can be bought: a sponsor cannot enter a table, reorder a row or change a mark, and there is no ranked position for sale. How the site is paid for, and the line each source of money does not cross, is set out under money and independence at /our-data#sec5.