> For the complete documentation index, see [llms.txt](https://help.tellius.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.tellius.com/tellius-6.3/getting-started/faqs/data-caching-faqs.md). # Data Caching FAQs Explore data caching FAQs to understand caching vs. ingestion, 'Copy to System,' Fast Query Engine, and performance optimization tips. This page contains a set of FAQs focused on the nuances of data caching within the Tellius platform. #### **1. How is data caching different from data ingestion in Tellius memory?** Data caching involves storing data in memory for quick access, ensuring faster response times for repeated queries. On the other hand, data ingestion refers to the process of bringing in data on demand, which may not be immediately stored in memory. While both processes are integral to Tellius, caching provides a performance advantage by reducing the need to repeatedly ingest data. #### **2. What happens if I disable data caching from these settings?** Disabling data caching can lead to performance issues. Each time you publish a dataset, create a Business View, or run Insights, Tellius will fetch the entire data from the source, apply necessary transformations, and then continue with subsequent operations. This can significantly slow down performance and exert undue pressure on the data source. #### **3. How is the "Copy to System" option different from data caching when creating a new scripted dataset or during data ingestion?** "Copy to System" refers to persisting data to the disk rather than just in memory. When this option is enabled, a copy of the data is saved on the disk. This ensures that even if the service restarts (which might clear the memory cache), the system doesn't have to retrieve data from the source again. #### **4. Are "Copy to Disk" and "Copy to System" the same?** Yes, **"Copy to Disk"** and **"Copy to System"** are synonymous. They might be represented differently in Settings and the Load page, but they perform the same function of saving data to disk. #### **5. How does enabling caching for insights and ML models help?** Caching saves datasets for faster access. However, Business Views are treated differently. Since both Insights and ML models use Business Views and go through the data multiple times, enabling caching makes these processes run much faster. Without caching, things could slow down noticeably. #### **6. What does the "Save to Fast Query Engine" setting mean for a dataset with BV enabled?** The "Save to Fast Query Engine" (FQE) setting determines whether a Business View should be saved to FQE by default. Unless there are specific issues with it, it is always recommended to save to FQE to ensure faster query performance. It's important to understand that some of these settings might evolve over time based on system upgrades and improvements. For instance, the option for "Copy to System" has been superseded in the 4.3 release with the introduction of the "Permanent Data Storage" feature, which always saves data to disk irrespective of user selection. --- # 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://help.tellius.com/tellius-6.3/getting-started/faqs/data-caching-faqs.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.