From 4ef86b2ff812a8d7074fe0cd35de27533a1e58b1 Mon Sep 17 00:00:00 2001 From: jielinxu Date: Tue, 22 Oct 2019 17:11:55 +0800 Subject: [PATCH] minor change Former-commit-id: 9e7e01ef8168c1c7d4f25fc67d9238fb1ef2ad4c --- README.md | 32 ++++++++++++++++++++++++-------- 1 file changed, 24 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 255b2553..153969bd 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -![Milvuslogo](https://github.com/milvus-io/docs/blob/branch-0.5.0/assets/milvus_logo.png) +![Milvuslogo](https://github.com/milvus-io/docs/blob/master/assets/milvus_logo.png) ![LICENSE](https://img.shields.io/badge/license-Apache--2.0-brightgreen) ![Language](https://img.shields.io/badge/language-C%2B%2B-blue) @@ -19,11 +19,11 @@ Milvus is an open source similarity search engine for massive feature vectors. D Milvus provides stable Python, Java and C++ APIs. -Keep up-to-date with newest releases and latest updates by reading Milvus [release notes](https://milvus.io/docs/en/Releases/v0.4.0/). +Keep up-to-date with newest releases and latest updates by reading Milvus [release notes](https://milvus.io/docs/en/Releases/v0.5.0/). -- GPU-accelerated search engine +- Heterogeneous computing - Milvus uses CPU/GPU heterogeneous computing architecture to process feature vectors, and are orders of magnitudes faster than traditional databases. + Milvus is designed with heterogeneous computing architecture for the best performance and cost efficiency. - Multiple indexes @@ -31,14 +31,30 @@ Keep up-to-date with newest releases and latest updates by reading Milvus [relea - Intelligent resource management - Milvus optimizes the search computation and index building according to your data size and available resources. + Milvus automatically adapts search computation and index building processes based on your datasets and available resources. -- Horizontal scalability +- Horizontal scalability - Milvus expands computation and storage by adding nodes during runtime, which allows you to scale the data size without redesigning the system. + Milvus supports online / offline expansion to scale both storage and computation resources with simple commands. + +- High availability + + Milvus is integrated with Kubernetes framework so that all single point of failures could be avoided. + +- High compatibility + + Milvus is compatible with almost all deep learning models and major programming languages such as Python, Java and C++, etc. + +- Ease of use + + Milvus can be easily installed in a few steps and enables you to exclusively focus on feature vectors. + +- Visualized monitor + + You can track system performance on Prometheus-based GUI monitor dashboards. ## Architecture -![Milvus_arch](https://github.com/milvus-io/docs/blob/master/assets/milvus_arch.jpg) +![Milvus_arch](https://github.com/milvus-io/docs/blob/master/assets/milvus_arch.png) ## Get started -- GitLab