Amazon AWS
DigitalOcean
Microsoft Azure
Linode
GoDaddy
Google Cloud Platform
Vultr
Heroku
Qdrant
Milvus
Weaviate
pgvecto.rs
Vespa.ai
txtai
Zilliz
ElasticSearch
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.
You could say a lot of things about AWS, but among the cloud platforms (and I've used quite a few) AWS takes the cake. It is logically structured, you can get through its documentation relatively easily, you have a great variety of tools and services to choose from [from AWS itself and from third-party developers in their marketplace]. There is a learning curve, there is quite a lot of it, but it is still way easier than some other platforms. I've used and abused AWS and EC2 specifically and for me it is the best.
Based on our record, Amazon AWS should be more popular than Qdrant. It has been mentiond 370 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.
Heroku runs on top of Amazon Web Services (AWS). Key benefits for me are:. - Source: dev.to / 9 days ago
First navigate to AWS at - https://aws.amazon.com create an account and then on the dashboard search for Amazon SES, click get started and then you should be directed to a dashboard like this. - Source: dev.to / 10 days ago
AWS Account Setup: If you don't have one, you can create a free account. - Source: dev.to / 14 days ago
Amazon Web Services is a leading cloud platform offering a vast array of services, from compute and storage to machine learning and IoT. AWS is known for its scalability, handling anything from small projects to enterprise-level applications. - Source: dev.to / 20 days ago
In this tutorial, I will walk you through building a quick static site by doing a static build using ReactJS & create-react-app, then show you how to deploy that static site on AWS using S3 buckets as well as how to cache it & add SSL certificates with CloudFront CDN & Certificate Manager. - Source: dev.to / 20 days ago
Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 3 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
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
Weaviate - Welcome to Weaviate
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!
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs