Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.
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Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
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Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
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Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, Ubuntu should be more popular than Qdrant. It has been mentiond 229 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
AgentCloud uses Qdrant as the vector store to efficiently store and manage large sets of vector embeddings. For a given user query the RAG application fetches relevant documents from vector store by analyzing how similar their vector representation is compared to the query vector. - Source: dev.to / 3 days ago
Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker. - Source: dev.to / 13 days ago
I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours. - Source: dev.to / 20 days ago
I'm currently looking to implement locally, using QDrant [1] for instance. I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2]. [1]. https://qdrant.tech/. - Source: Hacker News / about 1 month ago
There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb. - Source: Hacker News / 2 months ago
So, yeah, no .deb file, no curl/wget, no apt repository that they maintain. OK, cool 😎 no problem. I'll keep looking on Ubuntu side to see if Ubuntu has something 😁 you know. I could see that GNU Aspel's appendix does seem to have a recipe for how to make it myself if I wanted to go that route, as I pointed out earlier, however, since I have Ubuntu, I kept stomping the pavement and then it happened, I was able to... - Source: dev.to / 4 months ago
* As always, Ubuntu(https://ubuntu.com/) All solid, functional, and not treating you like cattle. - Source: Hacker News / 4 months ago
Yes, visit this website and install: https://ubuntu.com/. Source: 5 months ago
$ multipass shell server Welcome to Ubuntu 22.04.3 LTS (GNU/Linux 5.15.0-87-generic x86_64) * Documentation: https://help.ubuntu.com * Management: https://landscape.canonical.com * Support: https://ubuntu.com/advantage System information as of Fri Nov 10 01:32:53 CST 2023 System load: 0.0 Processes: 90 Usage of /: 30.9% of 4.67GB Users logged in: 0 ... - Source: dev.to / 6 months ago
The Linux installation is/was Ubuntu with an encrypted LUKS partition and before applying a week-old backup I thought that there might be a change of rescuing some data. Source: 7 months ago
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