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.
No features have been listed yet.
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.
No Vectara Neural Search videos yet. You could help us improve this page by suggesting one.
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.
If you like this tutorial, show your support by giving our Milvus GitHub repo a star ⭐—it means the world to us and inspires us to keep creating! 💖. - Source: dev.to / 3 months ago
Overview: Milvus is an open-source vector database designed for handling massive-scale vector data. It supports both NNS and ANNS and integrates well with various ML frameworks. - Source: dev.to / 10 months ago
If you enjoyed this blog post, consider giving us a star on Github and joining our Discord to share your experiences with the community. - Source: dev.to / 11 months ago
You can access the code on Github, feel free to ask questions on our Discord, and give us a star on Github. - Source: dev.to / 11 months ago
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 year ago
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
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
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
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
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
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.