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Weaviate VS Hugging Face

Compare Weaviate VS Hugging Face and see what are their differences

Weaviate logo Weaviate

Welcome to Weaviate

Hugging Face logo Hugging Face

The Tamagotchi powered by Artificial Intelligence 🤗
  • Weaviate Landing page
    Landing page //
    2023-05-10
  • Hugging Face Landing page
    Landing page //
    2023-09-19

Weaviate videos

Introducing the Weaviate Vector Search Engine!

More videos:

  • Review - Weaviate + Haystack presented by Laura Ham (Harry Potter example!)

Hugging Face videos

No Hugging Face videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Weaviate and Hugging Face)
Search Engine
100 100%
0% 0
AI
0 0%
100% 100
Utilities
100 100%
0% 0
Social & Communications
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Hugging Face should be more popular than Weaviate. It has been mentiond 257 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.

Weaviate mentions (28)

  • How to choose the right type of database
    Weaviate: An open-source, cloud-native vector database built for scalable and fast vector searches. It's particularly effective for semantic search applications, combining full-text search with vector search for AI-powered insights. - Source: dev.to / 3 months ago
  • 7 Vector Databases Every Developer Should Know!
    Weaviate is an open-source vector search engine with out-of-the-box support for vectorization, classification, and semantic search. It is designed to make vector search accessible and scalable, supporting use cases such as semantic text search, automatic classification, and more. - Source: dev.to / 4 months ago
  • Qdrant, the Vector Search Database, raised $28M in a Series A round
    Congrats to them! What have your experiences with vector databases been? I've been using https://weaviate.io/ which works great, but just for little tech demos, so I'm not really sure how to compare one versus another or even what to look for really. - Source: Hacker News / 5 months ago
  • How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
    A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving... - Source: dev.to / 5 months ago
  • Make Notion search great again: Vector Database
    To find semantically similar texts we need to calculate the distance between vectors. While we have just a few short texts we can brute-force it: calculate the distance between our query and each text embedding one by one and see which one is the closest. When we deal with thousands or even millions of entries in our database, however, we need a more efficient way of comparing vectors. Just like for any other way... - Source: dev.to / 7 months ago
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Hugging Face mentions (257)

  • Vector search in Manticore
    While looking into how to create text embeddings quickly and directly, we discovered a few helpful tools that allowed us to achieve our goal. Consequently, we created an easy-to-use PHP extension that can generate text embeddings. This extension lets you pick any model from Sentence Transformers on HuggingFace. It is built on the CandleML framework, which is written in Rust and is a part of the well-known... - Source: dev.to / 5 days ago
  • Understanding GPT: How To Implement a Simple GPT Model with PyTorch
    These libraries are fundamental for building and training our GPT model. PyTorch is a deep learning framework that provides flexibility and speed, while the Transformers library by Hugging Face offers pre-trained models and tokenizers, including GPT-2. - Source: dev.to / 10 days ago
  • Building a Simple Chatbot using GPT model - part 2
    Hugging Face is a company and community platform making AI accessible through open-source tools, libraries, and models. It is most notable for its transformers Python library, built for natural language processing applications. This library provides developers a way to integrate ML models hosted on Hugging Face into their projects and build comprehensive ML pipelines. - Source: dev.to / 18 days ago
  • Add Vector Search to Your Site
    We will use the OpenAI embeddings API to convert the content of the blog posts into vector embeddings. You will need to sign up for an API key on the OpenAI website to use the API. You will need to provide your credit card information as there is a cost associated with using the API. You can review the pricing on the OpenAI website. There are alternatives to generate embeddings. Hugging Face provides... - Source: dev.to / 17 days ago
  • How to run any LLM model with Hugging-Face 🤗
    Hugging-face 🤗 is a repository to host all the LLM models available in the world. https://huggingface.co/. - Source: dev.to / 24 days ago
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What are some alternatives?

When comparing Weaviate and Hugging Face, you can also consider the following products

Qdrant - Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

LangChain - Framework for building applications with LLMs through composability

Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.

Replika - Your Ai friend

pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs

Mitsuku - Browser-based, AI chat bot.