> ## Documentation Index
> Fetch the complete documentation index at: https://docs.neum.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# SupabaseSink

> SupabaseSink is designed to store and search vectorized data within Supabase databases, enabling efficient similarity searches and data management.

The `SupabaseSink` class provides the capabilities to interface with Supabase databases for the purpose of storing and querying vectorized data, which is essential for operations like semantic searches.

## Properties

Required properties:

* `database_connection`: The connection string necessary to connect to the Supabase database.
* `collection_name`: The name of the collection within the database where the vectors will be stored.

<CodeGroup>
  ```python Local Development
  from neumai.SinkConnectors import SupabaseSink

  # Initialize the SupabaseSink connector with the database connection string
  supabase_sink = SupabaseSink(
      database_connection = "postgresql://postgres:<password>@<host>:<port>/postgres",
      collection_name = "collection-name"
  )
  ```

  ```json Cloud
  {

      "sink": {
          "sink_name":"SupabaseSink",
          "sink_information":{
              "database_connection": "postgresql://postgres:<password>@<host>:<port>/postgres",
              "collection_name": "collection-name"
          }
      }
  }
  ```
</CodeGroup>