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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Qdrant's answer:
Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
Qdrant's answer:
Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
Qdrant's answer:
Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, DigitalOcean should be more popular than Qdrant. It has been mentiond 62 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.
Hey folks, it's been a while since I posted here! I've been quite busy with life, especially working at a few companies such as Hyperbeam, DigitalOcean, and a few others. That being said though, let's get into the real meat of today's topic. Why is C/C++'s development such a mess? - Source: dev.to / 11 months ago
Or create a VPS with linode.com, chunkhost.com, or digitalocean.com. Source: about 1 year ago
Linode (Mumbai) and DigitalOcean (Bangalore) each have a single DC in India, and Vultr has 3 (Mumbai, Bangalore, Delhi). Source: about 1 year ago
Or you could look at hosts like https://snakecrafthosting.comwhich is managed aka you upload your code and click start or if you want a whole server something like https://digitalocean.com. Source: about 1 year ago
In the same way that https://njal.la/ is different from https://digitalocean.com. Source: about 1 year ago
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 / 21 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 / about 1 month 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 / about 1 month 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 / 2 months ago
There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb. - Source: Hacker News / 3 months ago
Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.Sign up to Linode through SaaSHub and get a $100 in credit!
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.
Weaviate - Welcome to Weaviate
Vultr - VULTR Global Cloud Hosting - Brilliantly Fast SSD VPS Cloud Servers. 100% KVM Virtualization
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs