> For the complete documentation index, see [llms.txt](https://docs.powertable.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.powertable.com/explore-powertable/admin-portal/settings/writeback-settings/settings.md).

# Settings

In this section, all writeback-related settings can be configured by the admin.

<figure><img src="/files/1hHgTyfnExMKhepYKL0X" alt=""><figcaption><p>Writeback settings</p></figcaption></figure>

## 1. Allow users to configure database connections

Admins can enable or disable users from configuring database connections using this toggle button.

When disabled, no user can add a new connection to the PowerTable visual. They can only connect to the existing database connections that are already configured and available.

## 2. Request Time out <a href="#id-1.-request-time-out" id="id-1.-request-time-out"></a>

When PowerTable cannot connect to a database connection within a specified time limit, it displays a request timeout error. To avoid this, you can set a custom connection time from the admin console, which gives ample time for PowerTable to connect to a database before displaying a time-out error.

In the admin console, navigate to **Settings** and then Writeback > Settings. Under the **Writeback destination connection** settings, you can set the duration of the request time-out. In the image above, PowerTable will wait up to 60 seconds for the connection to be established before generating a request timeout error.

## 3. Batched Write Setting <a href="#id-2.-batched-write-setting" id="id-2.-batched-write-setting"></a>

By default, if your writeback payload exceeds 50k records, PowerTable can split the payload into multiple chunks, each of size 50k records, and write them back batch-by-batch.&#x20;

You can change the default batch size of 50k records in the **Batched Write Setting** section.&#x20;

The request time-out and batched write setting can be adjusted when you are working with high-volume data to achieve better performance.


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