> For the complete documentation index, see [llms.txt](https://docs.zerve.ai/guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zerve.ai/guide/canvas-view/assets/connections.md).

# Connections

Currently Zerve supports the following database connections with others following soon.

1. Snowflake
2. PostgreSQL
3. MySQL
4. MariaDB
5. BigQuery
6. Weaviate

## Setting up a Connection:

1. Go to Assets -> Connections -> Create Connections from your Zerve account's home page.

<figure><img src="/files/vGXNIPPY2UV8Can7P1hb" alt=""><figcaption><p>connection setup</p></figcaption></figure>

2. Select the required connection to setup and add the necessary connection parameters.

<figure><img src="/files/ynPuiTq8ffiuLRp18SSj" alt=""><figcaption><p>snowflake connection setup</p></figcaption></figure>

3. Once saved this connection can be accessed from SQL blocks in each canvas.

<figure><img src="/files/5Gvjf1LoAFy7Sgoof2J3" alt=""><figcaption><p>add connection asset to canvas</p></figcaption></figure>

4. Access the connection from SQL Block and store the queried table as df.

<figure><img src="/files/u6PW6sMiHFjnEkxDUNXo" alt=""><figcaption><p>connect from sql block</p></figcaption></figure>

5. Snowflake SQL query is executed and the result is stored as a dataframe in df variable.

<figure><img src="/files/TcmZYjceoKujpK2jgwgV" alt=""><figcaption><p>full screen mode of SQL Query</p></figcaption></figure>

This variable is now available for downstream python blocks as an input variable.&#x20;