> For the complete documentation index, see [llms.txt](https://v2.dataos.info/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://v2.dataos.info/concepts/resources/vulcan/components/advanced-features.md). # Advanced Features Advanced features help you extend Vulcan beyond standard model definitions. Use them when built-in behavior is close, but not enough. ## What this section covers Use this section when you need to: * make SQL more dynamic with macros * delay model execution until external conditions are ready * control how models materialize in the warehouse ## Quick selection guide Start with **Macros** when you want reusable SQL patterns. Use **Signals** when schedule timing depends on data readiness. Use **Custom materializations** when built-in model kinds do not fit. {% hint style="warning" %} These features add flexibility, but they also add maintenance overhead. Use them only when the standard workflow is not enough. {% endhint %} ## Choose a feature


Macros Use variables, built-ins, and templating to generate reusable SQL.	/pages/d18andQtLgpnuScKjZfu
Signals Add custom readiness checks before scheduled models run.	/pages/tghx7KvZotxwZk1VShJa
Custom materializations Define custom insert and lifecycle behavior for special execution patterns.	/pages/FelR44SySMj9ui6tbFgO

## When to use each feature ### Use macros when * SQL repeats across multiple models * values depend on execution context * templating keeps logic clearer than copy-paste ### Use signals when * upstream data arrives late or irregularly * schedules alone are not enough * model execution must wait for custom checks ### Use custom materializations when * built-in kinds cannot express the write behavior * the engine needs custom DDL or DML logic * you are prepared to maintain Python extension code ## Best practices Prefer built-in model kinds and scheduling first. Keep macros small, predictable, and easy to test. Use signals and custom materializations only for clear operational needs. --- # 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://v2.dataos.info/concepts/resources/vulcan/components/advanced-features.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.