> For the complete documentation index, see [llms.txt](https://docs.koinju.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.koinju.io/sql-cookbook/introduction.md).
# Introduction
Utilizing server-side computing can be particularly beneficial when processing indicators or backtesting with large datasets that can't fit on a user's disk or be loaded into RAM with conventional tools like pandas. This approach minimizes compute time on standard computers. With full access to public data tables in the database, users can not only retrieve market data but also execute computations directly on the server, harnessing the speed of our Clickhouse instance
### Example: Computing the sum, the average and the standard deviation of the quantity or ALL the orders done on BTC-USD on Coinbase from 2014.
This computation took 26s on our server and it's easy to see that this is handier than have to download a 835 millions rows long CSV file.
{% hint style="danger" %}
The users have limits for how many rows their query can read depending on their tier, this information is provided to you by Koinju and an error will be thrown by the database if you run queries that would go above the limit.
{% endhint %}
In the next chapter we will show how to run a backtest for a simple SMA strategy in seconds direcly inside the database.
---
# 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.koinju.io/sql-cookbook/introduction.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.