Software Alternatives & Reviews

Vector Vault VS Weaviate

Compare Vector Vault VS Weaviate and see what are their differences

Vector Vault logo Vector Vault

Unleash the full potential of Generative AI

Weaviate logo Weaviate

Welcome to Weaviate
Not present
  • Weaviate Landing page
    Landing page //
    2023-05-10

Vector Vault videos

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Weaviate videos

Introducing the Weaviate Vector Search Engine!

More videos:

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

Category Popularity

0-100% (relative to Vector Vault and Weaviate)
Databases
21 21%
79% 79
Search Engine
7 7%
93% 93
Platform As A Service (PaaS)
Utilities
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Weaviate seems to be more popular. It has been mentiond 28 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.

Vector Vault mentions (0)

We have not tracked any mentions of Vector Vault yet. Tracking of Vector Vault recommendations started around Jul 2023.

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 / 2 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 / 3 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 / 4 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 / 6 months ago
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What are some alternatives?

When comparing Vector Vault and Weaviate, 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/

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

Zilliz - Data Infrastructure for AI Made Easy

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

Pinecone - Search through billions of items for similar matches to any object, in milliseconds. It’s the next generation of search, an API call away.

Chroma - Welcome to Chroma Cutlery Cnife - Manufacturer of kitchen knives, includes products and contact information.