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README.md
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@ -1,36 +1,28 @@
<img src="https://zilliz-cms.s3.us-west-2.amazonaws.com/readme_en_6c5b3a1466.png" alt="milvus banner">
<div class="column" align="middle">
<a href="https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ">
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<img src="https://img.shields.io/github/license/milvus-io/milvus" />
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</a>
<img src="https://img.shields.io/github/license/milvus-io/milvus" alt="license"/>
<img src="https://img.shields.io/docker/pulls/milvusdb/milvus" alt="docker-pull-count" />
</div>
<div class="column" align="middle">
<a href="https://bestpractices.coreinfrastructure.org/projects/3563">
<img src="https://bestpractices.coreinfrastructure.org/projects/3563/badge" />
<img src="https://bestpractices.coreinfrastructure.org/projects/3563/badge" />
</a>
<a href="https://app.codacy.com/gh/milvus-io/milvus?utm_source=github.com&utm_medium=referral&utm_content=milvus-io/milvus&utm_campaign=Badge_Grade_Dashboard">
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</div>
## What is Milvus?
Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment.
Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. For more architecture datails, see [Milvus Architecture Overview](https://milvus.io/docs/v2.0.0/architecture_overview.md).
Milvus was released under the [open-source Apache License 2.0](https://github.com/milvus-io/milvus/blob/master/LICENSE) in October 2019. It is currently a graduate project under [LF AI & Data Foundation](https://lfaidata.foundation/).
## Key features
@ -40,19 +32,16 @@ Milvus was released under the [open-source Apache License 2.0](https://github.co
Average latency measured in milliseconds on trillion vector datasets.
</details>
<details>
<summary><b>Simplified unstructured data management</b></summary>
<li>Rich APIs designed for data science workflows.</li><li>Consistent user experience across laptop, local cluster, and cloud.</li><li>Embed real-time search and analytics into virtually any application.</li>
</details>
<details>
<summary><b>Reliable, always on vector database</b></summary>
Milvus’ built-in replication and failover/failback features ensure data and applications can maintain business continuity in the event of a disruption.
</details>
<details>
<summary><b>Highly scalable and elastic</b></summary>
Component-level scalability makes it possible to scale up and down on demand. Milvus can autoscale at a component level according to the load type, making resource scheduling much more efficient.
@ -63,21 +52,16 @@ Milvus was released under the [open-source Apache License 2.0](https://github.co
In addition to vectors, Milvus supports data types such as Boolean, integers, floating-point numbers, and more. A collection in Milvus can hold multiple fields for accommodating different data features or properties. Milvus pairs scalar filtering with powerful vector similarity search to offer a modern, flexible platform for analyzing unstructured data.
</details>
<details>
<summary><b>Unified Lambda structure</b></summary>
Milvus combines stream and batch processing for data storage to balance timeliness and efficiency. Its unified interface makes vector similarity search a breeze.
</details>
<details>
<summary><b>Community supported, industry recognized</b></summary>
With over 1,000 enterprise users, 7,500+ stars on GitHub, and an active open-source community, you’re not alone when you use Milvus. As a graduate project under the <a href="https://lfaidata.foundation/">LF AI & Data Foundation</a>, Milvus has institutional support.
</details>
## Quick start
### Install Milvus
@ -165,12 +149,10 @@ Interactive digital customer service that saves users time and businesses money.
Blazing fast similarity search, substructure search, or superstructure search for a specified molecule.
## Bootcamps
Milvus [bootcamp](https://github.com/milvus-io/bootcamp) are designed to expose users to both the simplicity and depth of the vector database. Discover how to run benchmark tests as well as build similarity search applications spanning chatbots, recommendation systems, reverse image search, molecular search, and much more.
## Contributing
Contributions to Milvus are welcome from everyone. See [Guidelines for Contributing](https://github.com/milvus-io/milvus/blob/master/CONTRIBUTING.md) for details on submitting patches and the contribution workflow. See our [community repository](https://github.com/milvus-io/community) to learn about our governance and access more community resources.
@ -344,14 +326,15 @@ The implemented SDK and its API documentation are listed below:
- [PyMilvus SDK](https://github.com/milvus-io/pymilvus)
- [Node SDK](https://github.com/milvus-io/milvus-sdk-node)
### Milvus insight
Milvus insight provides an intuitive and efficient GUI for Milvus.
- [Quick start](https://github.com/milvus-io/milvus-insight#quick-start)
### Milvus insight
Milvus insight provides an intuitive and efficient GUI for Milvus.
- [Quick start](https://github.com/milvus-io/milvus-insight#quick-start)
## Community
Join the Milvus community on [Slack](https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ) to share your suggestions, advice, and questions with our engineering team.
Join the Milvus community on [Slack](https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ) to share your suggestions, advice, and questions with our engineering team.
<a href="https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ">
<img src="https://zilliz-cms.s3.us-west-2.amazonaws.com/readme_slack_4a07c4c92f.png" alt="Miluvs Slack Channel" height="150" width="500">
@ -388,8 +371,6 @@ Reference to cite when you use Milvus in a research paper:
}
```
## Acknowledgments
Milvus adopts dependencies from the following:
@ -398,6 +379,3 @@ Milvus adopts dependencies from the following:
- Thanks to [etcd](https://github.com/coreos/etcd) for providing great open-source key-value store tools.
- Thanks to [Pulsar](https://github.com/apache/pulsar) for its wonderful distributed pub-sub messaging system.
- Thanks to [RocksDB](https://github.com/facebook/rocksdb) for the powerful storage engines.

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README_CN.md
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<img src="https://zilliz-cms.s3.us-west-2.amazonaws.com/readme_ch_69fbf0fc45.png" alt="Milvus banner">
<div class="column" align="middle">
<a href="https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ">
<img src="https://img.shields.io/badge/Join-Slack-orange" /></a>
<img src="https://img.shields.io/github/license/milvus-io/milvus" />
<img src="https://img.shields.io/docker/pulls/milvusdb/milvus" />
<a href="https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ">
<img src="https://img.shields.io/badge/Join-Slack-orange" alt="join-slack"/>
</a>
<img src="https://img.shields.io/github/license/milvus-io/milvus" alt="license"/>
<img src="https://img.shields.io/docker/pulls/milvusdb/milvus" alt="docker-pull-count" />
</div>
<div class="column" align="middle">
<a href="https://bestpractices.coreinfrastructure.org/projects/3563">
<img src="https://bestpractices.coreinfrastructure.org/projects/3563/badge" />
<img src="https://bestpractices.coreinfrastructure.org/projects/3563/badge" />
</a>
<a href="https://app.codacy.com/gh/milvus-io/milvus?utm_source=github.com&utm_medium=referral&utm_content=milvus-io/milvus&utm_campaign=Badge_Grade_Dashboard">
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<img src="https://api.codacy.com/project/badge/Grade/c4bb2ccfb51b47f99e43bfd1705edd95" />
</a>
</div>
# 欢迎来到 Milvus
## Milvus 是什么
@ -32,7 +25,6 @@ Milvus 是一款全球领先的开源向量数据库，赋能 AI 应用和向量
Milvus 2.0 是一款云原生向量数据库，采用存储与计算分离的架构设计。该重构版本的所有组件均为无状态组件，极大地增强了系统弹性和灵活性。更多系统架构细节，参考 [Milvus 系统架构](https://milvus.io/cn/docs/v2.0.0/architecture_overview.md)。
Milvus 基于 [Apache 2.0 License](https://github.com/milvus-io/milvus/blob/master/LICENSE) 协议发布，于 2019 年 10 月正式开源，是 [LF AI & Data 基金会](https://lfaidata.foundation/) 的毕业项目。
## 产品亮点
@ -42,19 +34,16 @@ Milvus 基于 [Apache 2.0 License](https://github.com/milvus-io/milvus/blob/mast
完成万亿条向量数据搜索的平均延迟以毫秒计。
</details>
<details>
<summary><b>简化的非结构化数据管理</b></summary>
<li>一整套专为数据科学工作流设计的 API。</li><li>无论是笔记本、本地集群还是云服务器，始终如一的跨平台用户体验。</li><li>可以在任何场景下实现实时搜索与分析。</li>
</details>
<details>
<summary><b>稳定可靠的用户体验</b></summary>
Milvus 具有故障转移和故障恢复的机制，即使服务中断，也能确保数据和应用的业务连续性。
</details>
<details>
<summary><b>高度可扩展，弹性伸缩</b></summary>
组件级别的高扩展性，支持精准扩展。
@ -65,20 +54,16 @@ Milvus 基于 [Apache 2.0 License](https://github.com/milvus-io/milvus/blob/mast
除了向量以外，Milvus还支持布尔值、整型、浮点等数据类型。在 Milvus 中，一个 collection 可以包含多个字段来代表数据特征或属性。Milvus 还支持在向量相似度检索过程中进行标量字段过滤。
</details>
<details>
<summary><b>基于 Lambda 架构的流批一体式数据存储</b></summary>
Milvus 在存储数据时支持流处理和批处理两种方式，兼顾了流处理的时效性和批处理的效率。统一的对外接口使得向量相似度查询更为便捷。
</details>
<details>
<summary><b>广受社区支持和业界认可</b></summary>
Milvus 项目在 GitHub 上获星超 6000，拥有逾 1000 家企业用户，还有活跃的开源社区。Milvus 由 <a href="https://lfaidata.foundation/">LF AI & Data 基金会</a> 背书，是该基金会的毕业项目。
</details>
## 快速开始
### 开始使用 Milvus
@ -87,7 +72,6 @@ Milvus 基于 [Apache 2.0 License](https://github.com/milvus-io/milvus/blob/mast
- [Cluster Quick Start Guide](https://milvus.io/cn/docs/v2.0.0/install_cluster-docker.md)
### 开发 Milvus
```bash
@ -145,8 +129,6 @@ $ make milvus
</tr>
</table>
#### 以图搜图系统
从海量图片中快速检索最相似图片。
@ -159,8 +141,6 @@ $ make milvus
迅速检索相似化学分子式。
## 训练营
Milvus [训练营](https://github.com/milvus-io/bootcamp)能够帮助你了解向量数据库的操作及各种应用场景。通过 Milvus 训练营探索如何进行 Milvus 性能测评，搭建智能问答机器人、推荐系统、以图搜图系统、分子式检索系统等。
@ -336,10 +316,9 @@ Milvus [训练营](https://github.com/milvus-io/bootcamp)能够帮助你了解
- [PyMilvus](https://github.com/milvus-io/pymilvus)
- [Node SDK](https://github.com/milvus-io/milvus-sdk-node)
## 社区
欢迎加入 [Slack](https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ) 频道分享你的建议与问题。你也可以通过 [FAQ](https://milvus.io/cn/docs/v1.0.0/performance_faq.md) 页面，查看常见问题及解答。
欢迎加入 [Slack](https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ) 频道分享你的建议与问题。你也可以通过 [FAQ](https://milvus.io/cn/docs/v1.0.0/performance_faq.md) 页面，查看常见问题及解答。
订阅 Milvus 邮件：
@ -374,8 +353,6 @@ Zilliz 是 Milvus 项目的幕后公司。我们正在 [招聘](https://app.moka
}
```
## 特别感谢
Milvus 采用了以下依赖库:
@ -384,4 +361,3 @@ Milvus 采用了以下依赖库:
- 感谢开源键值存储 [etcd](https://github.com/coreos/etcd)。
- 感谢分布式信息发布/订阅平台 [Pulsar](https://github.com/apache/pulsar)。
- 感谢存储引擎 [RocksDB](https://github.com/facebook/rocksdb)。