An introduction to the concepts related to vector database. By Frank Liu (@frankzliu)

Follow our step-by-step guide to perform a Milvus 2.1 benchmark by yourself. — Recently, we have updated the benchmark report of Milvus 2.1. Tests with a dataset of 1 million vectors have proved that QPS can be dramatically increased by merging small-nq queries. Here are some simple scripts for you to easily reproduce the tests. Procedures Deploy a Milvus standalone or cluster. In this…

A Python user-friendly Milvus version that makes installation more flexible. — This article is co-authored by Alex Gao and Angela Ni. Milvus is an open-source vector database for AI applications. It provides a variety of installation methods including building from source code, and installing Milvus with Docker Compose/Helm/APT/YUM/Ansible. Users can choose one of the installation methods depending on their operating systems…

Use string data to streamline the process of building your own similarity search applications. — Milvus 2.1 comes with some significant updates which make working with Milvus a lot easier. One of them is the support of string data type. Right now Milvus supports data types including strings, vectors, Boolean, integers, floating-point numbers, and more. This article presents an introduction to the support of string…

We are very glad to announce the release of Milvus 2.1 is now live after six months of hard work by all of our Milvus community contributors. This major iteration of the popular vector database emphasizes performance and usability, two most important keywords of our focus. We added support for…

Using similarity search technology to unlock the potential of unstructured data, even like wardrobes and its components! — If you are looking for a wardrobe to fit perfectly into your bedroom or fitting room, I bet most people will think of the made-to-measure ones. However, not everyone’s budget can stretch that far. Then what about those ready-made ones? The problem with this type of wardrobe is that they…

Learn about how Likee uses the vector database Milvus to identify duplicate videos in milliseconds. — This article is written by Xinyang Guo and Baoyu Han, engineers at BIGO, and translated by Rosie Zhang. BIGO Technology (BIGO) is one of the fastest-growing Singapore technology companies. Powered by artificial intelligence technology, BIGO’s video-based products and services have gained immense popularity worldwide, with over 400 million users in…

How is Zhentu’s detection system built with Milvus as its vector search engine? — In recent years, as e-commerce and online transactions become commonplace throughout the world, e-commerce fraud also flourished. By using computer-generated photos instead of real ones to pass identity verification on online business platforms, fraudsters create massive fake accounts and cash in on businesses’ special offers (e.g. …

Why consensus-based replication algorithm is not the silver bullet for achieving data consistency in distributed databases? — This article was written by Xiaofan Luan and transcreated by Angela Ni. Consensus-based replication is a widely-adopted strategy in many cloud-native, distributed databases. However, it has certain shortcomings and is definitely not the silver bullet. This post aims to first explain the concepts of replication, consistency, and consensus in a…