add content to v0.11

i18n/zh/docusaurus-plugin-content-docs/version-0.11/user-guide/integrations/mindsdb.md

@@ -0,0 +1,33 @@
+---
+keywords: [MindsDB, 机器学习平台, 数据库集成, 配置示例, SQL]
+description: 介绍如何使用 MindsDB 将 GreptimeCloud 实例集成到机器学习平台，并提供了配置示例。
+---
+
+# MindsDB
+
+[MindsDB](https://mindsdb.com/) 是一个开源的机器学习平台，使开发人员能够轻松地将
+先进的机器学习能力与现有数据库集成。
+
+使用 MindsDB 扩展，你的 GreptimeDB 实例可以开箱即用。
+你可以使用 MySQL 协议将 GreptimeDB 配置为 MindsDB 中的数据源：
+
+```sql
+CREATE DATABASE greptime_datasource
+WITH ENGINE = 'greptimedb',
+PARAMETERS = {
+  "host": "<host>",
+  "port": 4002,
+  "database": "<dbname>",
+  "user": "<username>",
+  "password": "<password>",
+  "ssl": True
+};
+
+```
+
+- `<host>` 是你的 GreptimeDB 实例的主机名或 IP 地址。
+- `<dbname>` 是你想要连接的数据库名称。
+- `<username>` 和 `<password>` 是你 [GreptimeDB 的鉴权信息](/user-guide/deployments/authentication/static.md)。
+
+MindsDB 是许多机器学习功能的优秀门户，包括您存储在我们实例中的时间序列数据的时间序列预测。
+访问 [MindsDB docs](https://docs.mindsdb.com/what-is-mindsdb) 了解更多。

i18n/zh/docusaurus-plugin-content-docs/version-0.11/user-guide/integrations/overview.md

@@ -11,3 +11,4 @@ GreptimeDB 可以与流行的数据写入、查询和可视化工具无缝集成
 import DocCardList from '@theme/DocCardList';
 
 <DocCardList />
+

i18n/zh/docusaurus-plugin-content-docs/version-0.11/user-guide/integrations/streamlit.md

@@ -0,0 +1,29 @@
+---
+keywords: [Streamlit, 数据应用, SQL 连接, MySQL 协议, Python]
+description: 使用 GreptimeCloud 和 Streamlit 构建数据应用的说明，包括创建 SQL 连接和运行 SQL 查询。
+---
+
+# Streamlit
+
+[Streamlit](https://streamlit.io/) 是一种更快的构建和分享数据应用的方式。
+可以基于 GreptimeDB 构建基于 Streamlit 的数据应用。
+
+你需要创建一个 SQL 连接在应用程序中使用 GreptimeDB 数据。
+由于 GreptimeDB 的 [MySQL 协议兼容性](/user-guide/protocols/mysql.md)，你可以在连接时将 GreptimeDB 视为 MySQL。
+
+以下是从 Streamlit 连接到 GreptimeDB 的示例代码片段：
+
+```python
+import streamlit as st
+
+st.title('GreptimeDB Streamlit 演示')
+conn = st.connection("greptimedb", type="sql", url="mysql://<username>:<password>@<host>:4002/<dbname>")
+
+df = conn.query("SELECT * FROM ...")
+```
+
+- `<host>` 是 GreptimeDB 实例的主机名或 IP 地址。
+- `<dbname>` 是要连接的数据库的名称。
+- `<username>` 和 `<password>` 是 [GreptimeDB 鉴权认证信息](/user-guide/deployments/authentication/static.md)。
+
+创建连接后，你可以对 GreptimeDB 实例运行 SQL 查询。结果集会自动转换为 Pandas dataframe，就像在 Streamlit 中使用普通数据源一样。

versioned_docs/version-0.11/user-guide/integrations/mindsdb.md

@@ -0,0 +1,35 @@
+---
+keywords: [MindsDB, machine learning, data source, configuration, SQL]
+description: Guide on configuring GreptimeCloud as a data source in MindsDB for machine learning capabilities.
+---
+
+# MindsDB
+
+[MindsDB](https://mindsdb.com/) is an open-source machine learning platform that
+enables developers to easily incorporate advanced machine learning capabilities
+with existing databases.
+
+Your GreptimeDB instance work out of box as using GreptimeDB extension with
+MindsDB. You can configure GreptimeDB as a data source in MindsDB using MySQL protocol:
+
+```sql
+CREATE DATABASE greptime_datasource
+WITH ENGINE = 'greptimedb',
+PARAMETERS = {
+  "host": "<host>",
+  "port": 4002,
+  "database": "<dbname>",
+  "user": "<username>",
+  "password": "<password>",
+  "ssl": True
+};
+
+```
+
+- `<host>` is the hostname or IP address of your GreptimeDB instance.
+- `<dbname>` is the name of the database you want to connect to.
+- `<username>` and `<password>` are your [GreptimeDB credentials](/user-guide/deployments/authentication/static.md).
+
+MindsDB is a great gateway for many machine learning features, including
+time-series forecasting, for your time series data stored in our instance. See
+[MindsDB docs](https://docs.mindsdb.com/what-is-mindsdb) for more information.

versioned_docs/version-0.11/user-guide/integrations/overview.md

@@ -11,3 +11,4 @@ The subsequent sections offer comprehensive guidance on integrating GreptimeDB w
 import DocCardList from '@theme/DocCardList';
 
 <DocCardList />
+

versioned_docs/version-0.11/user-guide/integrations/streamlit.md

@@ -0,0 +1,33 @@
+---
+keywords: [Streamlit, data apps, SQL connection, MySQL protocol, Python]
+description: Instructions for using GreptimeCloud with Streamlit to build data apps, including creating a SQL connection and running SQL queries.
+---
+
+# Streamlit
+
+[Streamlit](https://streamlit.io/) is a faster way to build and share data apps.
+It's possible to build streamlit based data apps based on GreptimeDB.
+
+To use GreptimeDB data in your application, you will need to create a SQL
+connection. Thanks to GreptimeDB's [MySQL protocol compatibility](/user-guide/protocols/mysql.md),
+you can treat GreptimeDB as MySQL when connecting to it.
+
+Here is an example code snippet to connect to GreptimeDB from Streamlit:
+
+```python
+import streamlit as st
+
+st.title('GreptimeDB Streamlit Demo')
+conn = st.connection("greptimedb", type="sql", url="mysql://<username>:<password>@<host>:4002/<dbname>")
+
+df = conn.query("SELECT * FROM ...")
+```
+
+- The `<host>` is the hostname or IP address of your GreptimeDB instance.
+- The `<dbname>` is the name of the database you want to connect to.
+- The `<username>` and `<password>` are your [GreptimeDB credentials](/user-guide/deployments/authentication/static.md).
+
+Once you have created the connection, you can run SQL query against your
+GreptimeDB instance. The resultset is automatically converted to Pandas
+dataframe just like normal data source in streamlit.
+