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.
No features have been listed yet.
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, Qdrant should be more popular than Case Law Access Project. It has been mentiond 40 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.
Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 4 days 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 / about 1 month 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 2 months 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
Harvard Library Innovation Lab | Multiple roles | Full time | Cambridge, MA (hybrid schedule, REMOTE possible) The Harvard Library Innovation Lab explores the future of libraries by building tools and communities for open knowledge. We build long term services like https://perma.cc, https://opencasebook.org, and https://case.law, and we host fellows like Molly White, creator of Web3 is Going Just Great. We are a... - Source: Hacker News / 12 months ago
This stuff has been in the case law for centuries. You maybe oughta go read the statutes and cases, okay? It ain't like Harvard Law School hasn't done their damnedest to make the case.law freely available to everyone. Source: about 1 year ago
Harvard Library Innovation Lab | Multiple roles | Full time | Onsite Cambridge, MA (hybrid schedule) The Harvard Library Innovation Lab explores the future of libraries by building tools and communities for open knowledge. We build long term services like https://perma.cc, https://opencasebook.org, and https://case.law, and we host fellows and technologists-in-residence like Molly White, creator of Web3 is Going... - Source: Hacker News / over 1 year ago
Use the Caselaw Access Project from Harvard: https://case.law/. It doesn't have everything but it has decent coverage of American case law. Source: over 1 year ago
SEEKING FREELANCER | Remote, must be US employment authorized The Harvard Library Innovation Lab builds open source websites to democratize access to information. We are seeking Vue + Django developers to add features to our projects: https://perma.cc, https://opencasebook.org, https://case.law Please send experience and hourly rates for public-interest open source work to the harvard.edu address in my profile. - Source: Hacker News / over 2 years ago
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Depict.ai - Amazon-quality product recommendations for any online store
Weaviate - Welcome to Weaviate
Collie CLI - One project on AWS, two on Azure, and might there be something on GCP too ๐ต?
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs
Google Scholar - Google Scholar is a freely accessible web search engine that indexes the full text of scholarly...