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.
Qdrant might be a bit more popular than memcached. We know about 40 links to it since March 2021 and only 30 links to memcached. 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.
One of the most effective ways to improve the application’s performance is caching regularly accessed data. There are two leading key-value stores: Memcached and Redis. I prefer using Memcached Cloud add-on for caching because it was originally intended for it and is easier to set up, and using Redis only for background jobs. - Source: dev.to / 13 days ago
Distributed caching Consistent hashing is a popular technique for distributed caching systems like Memcached and Dynamo. In these systems, the caches are distributed across many servers. When a cache miss occurs, consistent hashing is used to determine which server contains the required data. This allows the overall cache to scale to handle more requests. - Source: dev.to / about 1 month ago
Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs. - Source: dev.to / 4 months ago
Stores session state in a session store like Memcached or Redis. - Source: dev.to / 7 months ago
Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers. - Source: dev.to / 11 months ago
Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 7 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 2 months 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 / 3 months ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Weaviate - Welcome to Weaviate
Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs