Software Alternatives & Reviews

Vectara Neural Search VS Milvus

Compare Vectara Neural Search VS Milvus and see what are their differences

Vectara Neural Search logo Vectara Neural Search

Neural search as a service API with breakthrough relevance

Milvus logo Milvus

Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
  • Vectara Neural Search Landing page
    Landing page //
    2023-08-02
  • Milvus Landing page
    Landing page //
    2022-12-01

Milvus is a highly flexible, reliable, and blazing-fast cloud-native, open-source vector database. It powers embedding similarity search and AI applications and strives to make vector databases accessible to every organization. Milvus can store, index, and manage a billion+ embedding vectors generated by deep neural networks and other machine learning (ML) models. This level of scale is vital to handling the volumes of unstructured data generated to help organizations to analyze and act on it to provide better service, reduce fraud, avoid downtime, and make decisions faster.

Milvus is a graduated-stage project of the LF AI & Data Foundation.

Vectara Neural Search videos

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Milvus videos

End to End Tutorial on Milvus Lite

More videos:

  • Demo - An Introduction To the Milvus Open Source Vector Database

Category Popularity

0-100% (relative to Vectara Neural Search and Milvus)
Utilities
100 100%
0% 0
Search Engine
23 23%
77% 77
Vector Databases
0 0%
100% 100
AI
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Milvus should be more popular than Vectara Neural Search. It has been mentiond 34 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.

Vectara Neural Search mentions (13)

  • Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
    Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application. - Source: Hacker News / 3 months ago
  • Which LLM framework(s) do you use in production and why?
    You should also check us out (https://vectara.com) - we provide RAG as a service so you don't have to do all the heavy lifting and putting together the pieces yourself. Source: 5 months ago
  • Show HN: Quepid now works with vetor search
    Hi HN! I lead product for Vectara (https://vectara.com) and we recently worked with OpenSource connections to both evaluate our new home-grown embedding model (Boomerang) as well as to help users start more quantitatively evaluating these systems on their own data/with their own queries. OSC maintains a fantastic open source tool, Quepid, and we worked with them to integrate Vectara (and to use it to... - Source: Hacker News / 7 months ago
  • A Comprehensive Guide for Building Rag-Based LLM Applications
    RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just choosing a vector DB (last time I checked there were about 50), managing it, deciding on how to chunk data, etc. You also need to ensure your retrieval pipeline is accurate and fast, ensuring data is secure and private, and manage the whole thing as it... - Source: Hacker News / 8 months ago
  • Do we think about vector dbs wrong?
    I agree. My experience is that hybrid search does provide better results in many cases, and is honestly not as easy to implement as may seem at first. In general, getting search right can be complicated today and the common thinking of "hey I'm going to put up a vector DB and use that" is simplistic. Disclaimer: I'm with Vectara (https://vectara.com), we provide an end-to-end platform for building GenAI products. - Source: Hacker News / 8 months ago
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Milvus mentions (34)

  • Ask HN: Who is hiring? (April 2024)
    Zilliz (zilliz.com) | Hybrid/ONSITE (SF, NYC) | Full-time I am part of the hiring team for DevRel NYC - https://boards.greenhouse.io/zilliz/jobs/4307910005 SF - https://boards.greenhouse.io/zilliz/jobs/4317590005 Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most starred vector database on GitHub. Milvus is a distributed vector... - Source: Hacker News / about 1 month ago
  • Ask HN: Who is hiring? (February 2024)
    Zilliz is hiring! We're looking for REMOTE and/or HYBRID roles in SF Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus. - Source: Hacker News / 3 months ago
  • Qdrant, the Vector Search Database, raised $28M in a Series A round
    Congrats to Qdrant's team, $28M for a Series is really nice. There are a lot of OSS vector search databases out there, we could probably list the main ones: - Qdrant https://github.com/qdrant/qdrant - Milvus https://github.com/milvus-io/milvus What else? - Source: Hacker News / 4 months ago
  • Open Source Advent Fun Wraps Up!
    But before we do, I do want to say that 🤩 all these lovely Open-Source projects would love a little 🎉💕 love by getting a GitHub star ⭐ for their efforts. Including Open Source Milvus 🥰. - Source: dev.to / 4 months ago
  • Milvus Adventures Dec 15, 2023
    We are celebrating 25 different open source projects during the Open Source Advent this month! You can earn points all month long for a chance to win an exclusive swag pack from Zilliz and the participating projects! It’s a great chance to learn new skills and have some winter fun. Today is the first day and we are featuring Milvus! You can join us in our Discord channel or check us out on GitHub! We'd love a ⭐... - Source: dev.to / 5 months ago
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What are some alternatives?

When comparing Vectara Neural Search and Milvus, you can also consider the following products

txtai - AI-powered search engine

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/

Dify.AI - Open-source platform for LLMOps,Define your AI-native Apps

Weaviate - Welcome to Weaviate

Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.

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