Using SQLite to Store and Display Quantitative Trading Data
Summary
The article explains how FMZ’s built-in database interface, based on SQLite, can store structured strategy data when a simple persistence mechanism is insufficient. It introduces table creation and the basic operations for inserting, querying, updating, and deleting records, while cautioning users to avoid names reserved for platform tables. The database is presented as a lightweight option that requires no separate installation or configuration within the platform.
A worked example collects market tick fields into a table, queries records, changes and deletes sample rows, and displays the resulting data in a strategy status panel. The article also describes an in-memory mode whose contents reset when the trading bot restarts. It provides sample platform code and an operational walkthrough, but no benchmarks, reliability tests, or comparison of performance with other storage systems. Users should treat its claims about speed and suitability as descriptive rather than measured evidence, and consider persistence, data volume, and operational constraints for their own strategy.
Key ideas
- FMZ exposes a built-in SQLite-based interface for managing structured strategy data.
- The basic workflow uses SQL statements to create tables and insert, query, update, or delete records.
- A tick-data example stores market fields and displays queried rows in a strategy status panel.
- An in-memory mode loses its stored data when the bot restarts.
- The article gives no measured performance or reliability comparison with other databases.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.