Software Alternatives, Accelerators & Startups

Meta Search VS Weaviate

Compare Meta Search VS Weaviate and see what are their differences

Meta Search logo Meta Search

Search your Desktop, Google Drive, Dropbox, Gmail, Evernote.

Weaviate logo Weaviate

Welcome to Weaviate
  • Meta Search Landing page
    Landing page //
    2021-09-25
  • Weaviate Landing page
    Landing page //
    2023-05-10

Meta Search videos

No Meta Search videos yet. You could help us improve this page by suggesting one.

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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 Meta Search and Weaviate)
Productivity
100 100%
0% 0
Search Engine
0 0%
100% 100
Mac
100 100%
0% 0
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.

Meta Search mentions (0)

We have not tracked any mentions of Meta Search yet. Tracking of Meta Search recommendations started around Mar 2021.

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 / 4 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 / 5 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 / 6 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 / 6 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 / 8 months ago
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What are some alternatives?

When comparing Meta Search and Weaviate, you can also consider the following products

FYI - Find your documents, like magic 🔮

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/

Findo - Your smart search 🔍 assistant across personal cloud ☁️

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

Vaultedge - Access all your documents in one place.

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