> For the complete documentation index, see [llms.txt](https://docs.servoy.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.servoy.com/reference/servoy-developer/solution-explorer/all-solutions/active-solution/datasources.md).

# DataSources

## Overview

Servoy has three types of datasources:

* [Database datasource](/reference/servoy-developer/solution-explorer/resources/database-servers.md#overview) - this is the regular datasource, which can be any table or view from any database (that Servoy can connect using an JDBC driver)
* [In Memory datasource](/reference/servoy-developer/solution-explorer/all-solutions/active-solution/datasources/inmemory-datasources.md) - each solution has its special In Memory server , that can store tables with data.
* [View Foundsets datasource](/reference/servoy-developer/solution-explorer/all-solutions/active-solution/datasources/viewfoundsets-datasource.md#overview) - each solution has its special View Foundset server, that stores table definitions and can be loaded with data. This is similar to how SQL Views work except Servoy View Foundsets can be defined from Servoy Developer while SQL Views can only be defined(modified) from SQL (they are readonly in Servoy Developer)


---

# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.servoy.com/reference/servoy-developer/solution-explorer/all-solutions/active-solution/datasources.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.