Qdrant
Open-source, Rust-based vector database optimised for high-recall similarity search.
Qdrant is an open-source, Rust-based vector database optimised for high-recall similarity search. Open-source vector database implemented in Rust for high-performance, high-recall similarity search.
About Qdrant
Qdrant is an open-source vector database, written in Rust, for high-recall similarity search. It stores vectors and returns the closest matches to a query embedding.
Where it differs is combining vector similarity search with payload-based metadata filtering in a single query, so you can narrow results by structured fields at the same time as searching by similarity. You can self-host it via Docker images and standalone binaries on Linux, macOS, and Windows, or use the managed cloud service alongside the open-source deployment.
It fits teams building retrieval or RAG pipelines who want either a self-hosted store or a managed one. Self-hosted deployments need operational expertise for tuning, scaling, and monitoring, and the free cloud tier limits storage and cluster resources. It's purpose-built as a vector store, so it won't replace a general-purpose database.
Compared with other AI web apps in the directory, Qdrant is backend infrastructure for similarity search rather than an end-user application.
Sources: qdrant.tech, this listing
What it does well
- Open-source vector database implemented in Rust for high-performance, high-recall similarity search.
- Supports self-hosting via Docker images and standalone binaries on Linux, macOS, and Windows.
- Combines vector similarity search with payload-based metadata filtering in a single query.
- Offers a managed cloud service alongside the self-hosted open-source deployment.
Where it falls short
- Free cloud tier imposes limits on storage capacity and cluster resources.
- Self-hosted deployments require operational expertise for tuning, scaling, and monitoring.
- Purpose-built as a vector store rather than a general-purpose database.
Tagged
- Self-hostable
- CLI
- Web-based
- Enterprise Plan
- Free
- Freemium
- Open Source
Compared with similar things
Picked by shared tags inside the AI Web Apps.
- 01Freemium →Appsmith
Open-source low-code platform for internal apps, self-hostable and SOC2-certified.
- 02Freemium →Mage
AI-first data engineering platform — build, run, and monitor data pipelines with a chat-driven UI.
- 03Freemium →Hugging Face
Hub for ML models, datasets, and demos — the GitHub of open-source machine learning.
- 04Freemium →Invoke
Open-source Stable Diffusion suite with a professional canvas, ControlNet pipeline, and team features.
- 05Freemium →Weaviate
Open-source vector database with hybrid search and generative module integrations.
- 06Freemium →n8n
Open-source workflow automation with native LLM nodes — self-host on your own infrastructure.
Related reading
- How to Get Your First Users for a Vibe-Coded App
The cheapest way to get your first users for a vibe-coded app is organic short-video: post native-looking TikToks and Reels from accounts that read like your target user, and convert people in the comments — no ads, no influencers. It's slow at first and most clips flop, but it's how indie consumer apps go from zero to their first thousands of downloads.
Read guide → - How to Make Your App Go Viral with UGC
Going viral isn't luck — it's a format that earns watch time, run at volume. The founder of nomadtable grew it past a million downloads, solo, by ignoring view counts and chasing one number: how many people keep watching past the first three seconds. Here's that UGC playbook, with his real figures attributed throughout.
Read guide → - Where to Submit Your AI Tool
Submit your AI tool where people already search for one. Start with a niche AI tool directory (There's An AI For That, Futurepedia, and Vibedonalds for vibe-coded products), add a couple of general startup and SaaS directories, launch on one platform (Product Hunt or a smaller one like Uneed), and post in one community (a relevant subreddit or Show HN). Spread more directory submissions over the following weeks to get your first users.
Read guide →
Concepts you should know
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</a>Frequently asked questions
- What is Qdrant?
- Qdrant is an open-source, Rust-based vector database optimised for high-recall similarity search.
- Is Qdrant free?
- Qdrant offers a free tier and paid plans with higher limits or premium features.
- What platforms does Qdrant support?
- Qdrant runs on mac, win, linux, web.
- What category does Qdrant belong to?
- Qdrant is in the AI Web Apps category — Web apps with AI baked in — built for everything from journaling to research. Submitter-shipped products live here.
- What are the downsides of Qdrant?
- Free cloud tier imposes limits on storage capacity and cluster resources. Self-hosted deployments require operational expertise for tuning, scaling, and monitoring. Purpose-built as a vector store rather than a general-purpose database.