[skip ci] Simplified README with reference links

Milvus is an open source similarity search engine for massive-scale feature vectors. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.

Milvus provides stable Python, Java and C++ APIs.

Milvus provides stable Python, Java and C++ APIs. For more detailed introduction of Milvus and its architecture, see [Milvus overview](https://www.milvus.io/docs/en/aboutmilvus/overview/).

Keep up-to-date with newest releases and latest updates by reading Milvus [release notes](https://milvus.io/docs/en/release/v0.5.0/).

- Heterogeneous computing

  Milvus is built with heterogeneous computing architecture for the best performance and cost efficiency. 

- Multiple indexes

  Milvus supports a variety of indexing types that employs quantization, tree-based, and graph indexing techniques. 

- Intelligent resource management

  Milvus automatically adapts search computation and index building processes based on your datasets and available resources.

- Horizontal scalability

  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.png)

Keep up-to-date with newest releases and latest updates by reading Milvus [release notes](https://www.milvus.io/docs/en/release/v0.5.0/).

## Get started

#### Run Python example code

Make sure [Python 3.5](https://www.python.org/downloads/) or higher is already installed and in use.

Install Milvus Python SDK.

```shell

# Install Milvus Python SDK

$ pip install pymilvus==0.2.3

```

Create a new file `example.py`, and add [Python example code](https://github.com/milvus-io/pymilvus/blob/master/examples/advanced_example.py) to it.

Run the example code.

```shell

# Run Milvus Python example

$ python3 example.py

```

Please read [this page](https://www.milvus.io/docs/en/userguide/example_code/) for how to run an example program using Python SDK.

#### Run C++ example code

```

#### Run Java example code

Make sure Java 8 or higher is already installed.

Refer to [this link](https://github.com/milvus-io/milvus-sdk-java/tree/master/examples) for the example code.