Weaviate

Name: Weaviate
Rating: 4.83 (12 reviews)

The AI-native database for a new generation of software

4.8•12 reviews•

47 followers

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AI Infrastructure Tools•AI Databases

The AI-native database for a new generation of software. Store and retrieve data objects and vector embeddings. Seamlessly connect to your favorite ML models. And build intuitive, reliable AI applications that scale.

Free

Launch tags:

Developer Tools•Artificial Intelligence•GitHub

Launch Team

Bob van Luijt

Maker

Hi developers, data scientists, and all those interested in ML & AI 👋 I'm Bob, one of the co-founders of SeMI Technologies. I'm super excited to share the vector search engine Weaviate with you today on PH. We've created Weaviate because we believe that there was a need for a new type of search engine (or database) with machine learning at its core. The video above will give you an overview of the functionality of Weaviate, but you can also try it yourself by going to our Github or documentation. If you are a developer looking for a more detailed explanation of what Weaviate is: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.). It offers Semantic Search, Question-Answer-Extraction, Classification, Customizable Models (PyTorch/TensorFlow/Keras), and more. Built from scratch in Go, Weaviate stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance of a cloud-native database, all accessible through GraphQL, REST, and various language clients. You can follow us on Github, Twitter, or LinkedIn and you can join our Slack or Meetup groups. Github: https://github.com/semi-technolo... Slack: https://link.semi.technology/3d3... Documentation: https://www.semi.technology/deve... We love to hear what you think! Cheers

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4yr ago

Leo

Tesla Reader

I've been watching the space for semantic document search for quite some time now. I've worked with many systems - Elastic Search, Jina, Haystack, GPT-3 semantic search... you name it. They are either limited in what they can do or how much data they can handle, are very expensive to run, hard to set up, or take a long time to process queries. That's why I've continually been searching for better solutions. And that's how I found Weaviate. This system is the first where I'm actually up and running within a day. It can search through Gigabytes of text within a fraction of a second. I don't need an expensive GPU server to get good search results. And setting up the database, ingesting documents and querying the index in Python just takes a few lines of code. It's a really clean and elegant solution. To me, using Weaviate feels like using Stripe. It's fast, it's fun, and it just works. And that is awesome, because it means that the search itself is taken care of, and I can focus on building on top of it.

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4yr ago

Bob van Luijt

Maker

@leoplusx1 wow! Thank you for your kind words! 😊🙏 If you ever do find anything, please don't hesitate to let us know. Again, thanks!

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4yr ago

Do you use Weaviate?

4.8

Based on 12 reviews

Review Weaviate?

Weaviate is praised for its robust vector database capabilities, enabling efficient data management and retrieval. Makers of Findr highlight its ability to create vector stores dynamically and provide excellent support. Zefi.ai appreciates Weaviate's consistent support and data management features. Insight7 values its fast semantic search and scalability, essential for real-time insights. Overall, Weaviate is recognized for its AI-native design, flexibility, and seamless integration, making it a preferred choice for building scalable AI applications.

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