Bun.sh
Deno
Zig
Node.js
Next.js
.NET Core
FastAPI
Webpack
Qdrant
Milvus
Weaviate
pgvecto.rs
Vespa.ai
txtai
Zilliz
ElasticSearch
Bun is a new JavaScript runtime built from scratch to serve the modern JavaScript ecosystem. It has three major design goals:
Speed. Bun starts fast and runs fast. It extends JavaScriptCore, the performance-minded JS engine built for Safari. As computing moves to the edge, this is critical.
Elegant APIs. Bun provides a minimal set of highly-optimimized APIs for performing common tasks, like starting an HTTP server and writing files.
Cohesive DX. Bun is a complete toolkit for building JavaScript apps, including a package manager, test runner, and bundler.
Bun is designed as a drop-in replacement for Node.js. It natively implements hundreds of Node.js and Web APIs, including fs, path, Buffer and more.
The goal of Bun is to run most of the world's server-side JavaScript and provide tools to improve performance, reduce complexity, and multiply developer productivity.
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.
QdrantNo 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, Bun.sh should be more popular than Qdrant. It has been mentiond 143 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.
In this third and final article in the series on HTML Streaming, we will explore the practical implementation of the Diff DOM Streaming library in web browsing. This approach will allow any website using web components to retain its state during browsing. We will discuss in detail how to achieve this step by step using VanillaJS and Bun. - Source: dev.to / 11 days ago
At Node Conference 2023, Jarred Sumner (creator of Bun) showed a demo of server components in Bun, so there is at least partial support in that ecosystem. The Bun repo provides bun-plugin-server-components as the official plugin for server components. And while I haven’t looked at it in-depth, Marz claims to be a “React Server Components Framework for Bun”. - Source: dev.to / 21 days ago
Continuously evolving, Bun is currently optimized for MacOS and Linux, with ongoing efforts towards Windows compatibility. Tailored for resource-constrained environments like serverless functions, it emerges as an ideal solution. The Bun team is committed to achieving comprehensive Node.js compatibility and seamless integration with prevalent frameworks. For those intrigued by Bun's potential and want to give it a... - Source: dev.to / about 1 month ago
Let’s say you are interested in learning more about Bun and probably give it a try. Bun has a website, where you can learn more about Bun and its features (including all the benchmark data captured in this issue), and here is the link. - Source: dev.to / about 1 month ago
Install Node.js (or Bun, or Deno, or whatever JS runtime you prefer) if it's not there. - Source: dev.to / 2 months 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 / 5 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 / 12 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 / about 2 months ago
Initialize the Qdrant Client with in-memory storage. The collection name will be “imagebind_data” and we will be using cosine distance. - Source: dev.to / 2 months ago
Deno - A secure runtime for JavaScript and TypeScript built with V8, Rust, and Tokio.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Zig - Zig is a general-purpose programming language designed for robustness, optimality, and maintainability.
Weaviate - Welcome to Weaviate
Node.js - Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs
