> For the complete documentation index, see [llms.txt](https://docs.verbdata.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.verbdata.com/data-sources/data-synchronization/schemaless-and-nosql.md). # Schemaless & NoSQL Verb's platform treats all data uniformly whether the data source is a traditional RDBMS or a document/schemaless database. In the case of an RDBMS system, the relationships are explained through the database schema via primary and foreign, constraints, and indices. In the case of schemaless, document-centric, or NoSQL databases, the concept of a schema is implied by the contents of the documents in the database. In order to allow you to build robust models (even between multiple data sources), Verb transposes your schemaless data source into oarent and child tables during the ingestion process. For example if your database stores customer documents that have an array of customer orders, Verb will create 2 schema objects with an implied relationship between them. In doing so, you can use the Verb model editor and dashboard creator to build queries and visualizations that join parent documents to descendant documents. --- # 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, and the optional `goal` query parameter: ``` GET https://docs.verbdata.com/data-sources/data-synchronization/schemaless-and-nosql.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.