Software Alternatives, Accelerators & Startups

Milvus VS Vectara Neural Search

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

Milvus logo Milvus

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

Vectara Neural Search logo Vectara Neural Search

Neural search as a service API with breakthrough relevance
  • 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 Landing page
    Landing page //
    2023-08-02

Milvus features and specs

  • High Performance
    Milvus is designed to manage and process large-scale vector data extremely fast, making it suitable for handling real-time processing of massive datasets.
  • Scalability
    Milvus supports horizontal scaling, ensuring that as the data grows, the system can scale out by adding more nodes to maintain performance.
  • Flexible Deployment
    Milvus can be deployed on-premises, on cloud services, or in hybrid environments, providing flexibility for different infrastructure needs.
  • Community and Support
    As an open-source project, Milvus has a strong community and support network, including comprehensive documentation and active community forums.
  • Rich Ecosystem
    Milvus integrates well with various machine learning and data processing tools, such as TensorFlow, PyTorch, and other AI frameworks, facilitating seamless workflows.
  • Built-in Indexing
    Milvus provides built-in indexing capabilities like IVF, HNSW, and ANNOY, which enhance the speed and efficiency of similarity searches on vector data.

Vectara Neural Search features and specs

No features have been listed yet.

Analysis of Milvus

Overall verdict

  • Milvus is generally regarded as a good option, especially for businesses and developers working in the field of AI and data science. Its open-source nature allows for flexibility and community support, and it is backed by a solid architecture designed for scalability and efficiency.

Why this product is good

  • Milvus is considered a strong choice for handling large-scale vector data due to its high-performance capabilities and ability to manage similarity search effectively. It is particularly well-suited for applications involving AI, machine learning, and deep learning where vector operations are common.

Recommended for

    Milvus is ideal for data scientists, AI researchers, and engineers who require efficient and scalable vector search solutions. It is also recommended for companies and projects dealing with recommendation systems, image and video search, natural language processing, and more.

Milvus videos

End to End Tutorial on Milvus Lite

More videos:

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

Vectara Neural Search videos

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

Add video

Category Popularity

0-100% (relative to Milvus and Vectara Neural Search)
Search Engine
100 100%
0% 0
Utilities
0 0%
100% 100
Custom Search Engine
100 100%
0% 0
Communications
0 0%
100% 100

User comments

Share your experience with using Milvus and Vectara Neural Search. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Milvus should be more popular than Vectara Neural Search. It has been mentiond 38 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.

Milvus mentions (38)

View more

Vectara Neural Search mentions (16)

  • Show HN: Create RAG-powered pages to get answers from your docs– without coding
    Hey folks! I wanted to share one of the latest projects I worked on, called Vectara Portal. It's an application that allows users of our platform (https://vectara.com/) to create shareable pages that let you and other users (privately, if you wish) chat with, search through, or get answers from your documents. This began as a side project resulting from a question over lunch: "How do we put the power of our... - Source: Hacker News / 9 months ago
  • Show HN: New and more powerful OSS hallucination detection
    Hi HN! At Vectara (https://vectara.com) were hyper focused on providing best in class retrieval-augmented-generation. We've just released a new open source hallucination detection model (available on HuggingFace and Kaggle) and associated leaderboard to show which LLMs are best at producing accurate summaries. It's far more accurate than our previous model, which has been referenced by a number of HN users here... - Source: Hacker News / 10 months ago
  • Ask HN: Who is hiring? (August 2024)
    Vectara (https://vectara.com) | Field Engineer, Front-end Engineer, Platform (back-end) Engineer, and Product Managers | Full-time | Egypt, Pakistan, and/or Remote (depends on position) Vectara is a retrieval augmented generation (RAG) as a service platform. We have a ton of IP already: an embedding model that outperforms Cohere and OpenAI, a reranking model that does similarly, a generative model that... - Source: Hacker News / 10 months ago
  • 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 / over 1 year 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: over 1 year ago
View more

What are some alternatives?

When comparing Milvus and Vectara Neural Search, 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/

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

Vespa.ai - Store, search, rank and organize big data

txtai - AI-powered search engine

TopK.io - TopK is a cloud-native database intended for search use cases. It comes with keyword search, vector search, and metadata filtering built-in. Easy-to-use search engine loved by developers of all skill levels.

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