Firstly, welcome, and thanks for your interest in [Milvus](https://milvus.io)! No matter who you are, what you do, we greatly appreciate your contribution to help us reinvent data science with Milvus.
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## What is Milvus
Milvus is an open source vector search engine that makes incredibly fast querying speed enhancement over current solutions of massive vector processing. Built on optimized indexing algorithm, it is compatible with major AI/ML models.
Milvus was developed by researchers and engineers in ZILLIZ, a tech startup that intends to reinvent data science, with the purpose of providing enterprises with efficient and scalable similarity search and analysis of feature vectors and unstructured data.
Milvus provides stable [Python](https://www.tensorflow.org/api_docs/python) and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as RESTful API.
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- GPU-accelerated search engine
Milvus is designed for the largest scale of vector index. CPU/GPU heterogeneous computing architecture allows you to process data at a speed 1000 times faster.
- Intelligent index
With a “Decide Your Own Algorithm” approach, you can embed machine learning and advanced algorithms into Milvus without the headache of complex data engineering or migrating data between disparate systems. Milvus is built on optimized indexing algorithm based on quantization indexing, tree-based and graph indexing methods.
- Strong scalability
The data is stored and computed on a distributed architecture. This lets you scale data sizes up and down without redesigning the system.
## Get started
### Install and start Milvus server
#### Use Docker
Use Docker to install Milvus is a breeze. See the [Milvus install guide](doc/master/userguide/install_milvus.md) for details.
#### Use source code
##### Compilation
###### Step 1 Install necessary tools
```shell
# Install tools
Centos7 :
$ yum install gfortran qt4 flex bison mysql-devel mysql
To edit Milvus settings in `conf/server_config.yaml` and `conf/log_config.conf`, please read [Milvus Configuration](milvus-io/milvus/doc/master/reference/milvus_config.md).
### Try your first Milvus program
#### Run Python example code
Make sure [Python 3.4](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==0.2.0
```
Create a new file `example.py`, and add [Python example code](https://github.com/milvus-io/pymilvus/blob/branch-0.3.1/examples/AdvancedExample.py) to it.
Run the example code.
```python
# Run Milvus Python example
$python3example.py
```
#### Run C++ example code
```shell
# Run Milvus C++ example
$ cd[Milvus root path]/cpp/milvus/bin
$ ./sdk_simple
```
## Contribution guidelines
Contributions are welcomed and greatly appreciated. If you want to contribute to Milvus, please read the [contribution guidelines](CONTRIBUTING.md). This project adheres to the [code of conduct](CODE OF CONDUCT.md) of Milvus. By participating, you are expected to uphold this code.
We use [GitHub issues] to track issues and bugs. For general questions and discussions, please go to [Milvus Forum].
## Join the Milvus community
For public discussion of Milvus, please join our [discussion group].
## Milvus Roadmap
Please read our [roadmap](milvus-io/milvus/doc/master/roadmap.md) to learn about upcoming features.
