> For the complete documentation index, see [llms.txt](https://docs.getdot.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.getdot.ai/integrations/databases.md). # Databases Connect Dot to your data warehouse ## Removing a connection Removing a connection keeps the work you put into your tables. Tables that were switched on are archived instead of deleted, so their descriptions and column comments stay with them. Reconnect the same warehouse and Dot restores those tables on the next sync, and switches them back on. It matches them by database, schema, and table name, not by the old connection, so re-adding the same warehouse under a different host still works. Tables that were switched off are removed for good, together with the queries saved against them. An archived table stays visible on the Model page with a note explaining that it is no longer reachable. From there you can leave it for a future reconnect, or click **Delete Permanently** to remove it. {% hint style="warning" %} The remove dialog has a checkbox, **Also delete table setup**. Tick it only if you want the descriptions, the column comments, and the record of which tables were on to be gone for good. Reconnecting does not bring them back. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.getdot.ai/integrations/databases.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.