What does HackerNews think of qdrant?

Real-time data access in Grok is powered by Qdrant, an open-source Vector DB.

https://twitter.com/qdrant_engine/status/1721097971830260030

https://github.com/qdrant/qdrant

Made available in Qdrant v1.5 https://github.com/qdrant/qdrant

Qdrant | REMOTE | Full-time | https://qdrant.tech | https://github.com/qdrant/qdrant

Qdrant is a leading open-source Vector Database provider.

We are Looking for Technical Writer, Integrations Engineer, Database Tester, Developer Advocate(s).

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Awesome work!

At Qdrant we do this at scale. Store billions of vectors in a cluster of any size. Also in Rust which turned out to be an amazing choice, and fully open source. It uses various features to keep things performant, such as vectorization (multiple arches), quantization (form of compression) and more.

https://github.com/qdrant/qdrant

It depends on your requirements, for a simple hybrid-search solution, elastic, etc. should be enough. With growing data amount and if working not only with text embeddings, you should try out a dedicated solution, like Qdrant. https://github.com/qdrant/qdrant (Disclaimer, I'm from the team)

Qdrant, is the most popular, high-performance native vector db, written in Rust

https://github.com/qdrant/qdrant

(disclaimer: part of the team)

Made with Qdrant Vector Database https://github.com/qdrant/qdrant

Cohere embed API https://docs.cohere.com/reference/embed

and AWS Lambda

We at Qdrant are glad to be a part of this awesome solution, providing the Vector Database resource for Danswer. https://github.com/qdrant/qdrant

This can be achieved with open-source solutions like Qdrant.https://github.com/qdrant/qdrant

Qdrant, Remote-first, HQ in Berlin, hiring worldwide, Visa sponsorship.

Qdrant is an open-source Vector Database written in Rust 🦀. Also, available as a managed cloud solution (DBaaS). https://github.com/qdrant/qdrant

- DevRel Manager(s)

- Cloud Engineers (AWS,GCP,Azure)

Also, looking for paid open-source contributors. Strong Rust skills are required. 🦀 https://qdrant.to/jobs

You could check Qdrant, a dedicated Vector Database with advanced features. https://github.com/qdrant/qdrant Disclaimer: I'm from the Qdrant Team.

Thanks for mentioning Qdrant. https://github.com/qdrant/qdrant

You can do everything with PostGres:

Full-text search, but there are better engines for it: Elastic, Meilisearch, etc. right?

You can also store JSON into Postgres, but you should better use MongoDB for NoSQL purposes, right?

The reason for this is: dedicated tools are always better, faster, and more feature-rich.

The ANN index IVF implemented in pgvector has very poor performance, with only around 50% recall. Is it something you are looking for?

Disclaimer: I'm a co-founder at Qdrant, an open-source vector database written in Rust. https://github.com/qdrant/qdrant

PS: Chroma isn't a database but а Python wrapper around ClickHouse DB.

I forgot about https://github.com/qdrant/qdrant. It's a DB not a library so again may not be an exact answer for what you're looking for

That is amazing! Would be awesome to have a client-side version of Qdrant https://github.com/qdrant/qdrant

tbh. Looks like a huge overengineered legacy project. What is the clue to having all these ANN indexes in place? Is it a kinda art collection? What is the sense when you can just have HNSW in memory, with quantization, or on disk, GPU accelerated, etc. There are already better alternatives like Qdrant, which is written in Rust and super performant https://github.com/qdrant/qdrant, or Weaviate with GraphQL interface https://github.com/weaviate/weaviate

Why did you decide to use a closed-source vector database if you do open-source? There are plenty of open-source solutions to choose from: Weaviate, Milvus, or Qdrant. https://github.com/qdrant/qdrant Disclaimer: I'm from the Qdrant team.

Qdrant, worth checking if you are looking for open-source alternative to Pinecone. (I‘m affiliated ) https://github.com/qdrant/qdrant

Nowadays, there are more convenient tools for building a search engine. For example, Rust. :) https://github.com/qdrant/qdrant

You can also do so using an open-source vector database like Qdrant https://github.com/qdrant/qdrant

Yes, there are more suitable solutions than faiss or annoay. For example https://github.com/qdrant/qdrant

Great work! Instead of faiss, you could use a standalone vector search engine like Qdrant https://github.com/qdrant/qdrant It would bring some advantages like, for example, filtering support.

Qdrant is a vector search engine written entirely in Rust https://github.com/qdrant/qdrant

Qdrant | https://qdrant.tech | Full-time | Remote (global) | Rust Engineers Qdrant is an advanced Vector Search Engine. It is open-source and written in Rust. Check it out on GitHub. https://github.com/qdrant/qdrant We develop both the project itself as well as the AI solutions built on its basis. We are looking for Rust developers to support us with the development of new engine features and to take care of performance improvements. Apply here https://join.com/companies/qdrant/6170562-rust-system-develo...