> For the complete documentation index, see [llms.txt](https://navixy.com/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://navixy.com/docs/qna/on-premise/where-and-how-is-data-stored.md). # Where and how is data stored? MySQL database stores tracking and business data. Images stored in API-server subdirectories. Two databases: tracking and google ## Where is the data stored? All tracking, telematics and business data is stored in a MySQL database deployed on the server where Navixy application is running or on a dedicated server. In addition, all images uploaded in the web interface (branding, avatars, submitted photos in forms, etc.) are stored in the API-server subdirectories on the application server. ## How is the data stored in the database? All the acquired data is organized into two databases: * tracking - contains points received from trackers (coordinates, time, satellites, direction, data on inputs and outputs, etc.). * google - contains all created entities, user and device settings, rules, reports, sensor and counter data, other business data, and anything not directly related to tracking points received from devices. The detailed table structure can be checked in the platform build by examining the deployment scripts in the `/db` subdirectory. ## How can I export data from the database? If you need to export data, it can be done using the common `SELECT` SQL statement. Due to the large number of tables and the variety of data, we recommend contacting the Technical Solutions department for advice on where to take data from and what SQL queries to use. --- # 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://navixy.com/docs/qna/on-premise/where-and-how-is-data-stored.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.