Story of junior analyst who built a data tool with AI: free online converter SQLite to Excel or CSV

When working with structured data, one common need arises in converting between SQLite databases and CSV or Excel (XLSX) files. This is exactly what happened to Maria, who is a data analysis clerk at a mid-sized regional company. She doesn’t write code, she doesn’t know what JavaScript, WebAssemble, or PapaParse is. Her work lived in Excel, and she’s found herself bumping up against limitations she didn’t expect.

So when data arrived in an .sqlite format instead of simple CSV or XLSX, Maria found herself staring at files she couldn’t open — let alone use. Her job didn’t change. The report was still due. But now, the data was locked in files she couldn’t access. With no human help in sight, Maria armed herself with AI and developed her own free online SQLite to XLSX / CSV converter.

When the software you need doesn’t exist — write it into existence

The locked data couldn’t be ignored, so Maria tried the usual paths — googling for a software that fits her requirement.

Maria wasn’t the first to face this problem. She searched online, only to find forums filled with shady programming products. There were solutions — expensive desktop tools, third-party web apps. She even found one converter that almost worked… but provided no useful outcome.

She realized that even though tools existed, none were meant for her. Maria didn’t want to give up or wait for someone else to solve her problem. She wanted something simple, private, and immediate.

She thought, “Why can’t I just make my own free online data converter?”

That’s when AI helped. With nothing more than her browser and a few clicks, she got a tool that uploads an SQLite file and instantly turns it into a usable Excel spreadsheet or CSV file.

From problem to prototype: building her own solution

It was during a casual conversation with an AI assistant that Maria began to piece together an idea. She described her issue. The AI replied with concepts she didn’t fully understand, but it confirmed data format conversion can be done directly in browser.

Using suggestions and explanations form AI, Maria cobbled together a simple HTML file. The result became something she shared with everyone onlie, quietly titled: SQLite to CSV/Excel XLSX Converter.

The core of Maria’s converter: three JS libraries

Maria’s tool was built around three robust open-source JavaScript libraries. Existence of these libraries and their public availability is what made Maria’s project feasible as a browser tool.

Library 1 — sql-wasm.js

SQL-WASM.JS is the main library that brings SQLite, a compact yet powerful database engine written in C, into the browser through WebAssembly — a low-level format designed for optimal performance on web platforms.

SQL.js originated from the process of compiling SQLite’s original C code using Emscripten, a technology that converts C and C++ programs into WebAssembly. The result is a fully operational, server-independent SQLite environment running seamlessly inside a browser tab — exactly what Maria’s project required.

This library allowed Maria’s tool to process and query .sqlite files entirely within the her browser.

Library 2 — xlsx.js

Having through SQL.js established in a browser tab a connection to the data stored inside .sqlite file, Maria needed to convert the data in Excel format. AI suggested to use xlsx.js (SheetJS) library.

SheetJS was established in the early 2010s as a grassroots initiative aimed at enabling JavaScript-based Excel file manipulation. It allowed users to create, parse, and export .xlsx files without requiring Microsoft Office or external servers.

Maria’s tool leveraged SheetJS as its core mechanism for converting structured data into Excel format.

Library 3 — papaparse.js

Wanting for her tool to be more versatile, Maria has asked for CSV format support in her tool. AI suggested using PapaParse — one of the fastest and most reliable CSV parsers in JavaScript.

Together, these three libraries formed a cohesive and powerful backbone of a simple browser based online converter. All tasks executed entirely within the browser.

What Maria built and how it works

The tool Maria created was entirely browser-based, meaning it worked without installing any software and without sending any files online. External libraries used in this project are loaded for local use. The tool informs on successful loading of libraries.

The tool was designed around two key use cases:

Converting a SQLite database into a readable Excel or CSV file.
Turning a spreadsheet or CSV into a new SQLite database.

Let’s break down how it actually works:

Frontend design

Maria’s application is written in plain HTML, JavaScript, and CSS. It has a clean, accessible interface:

Drag-and-drop areas for files.
Dynamic previews of table content.
Tabs for switching between conversion directions.
Responsive feedback on progress and success/failure.

The conversion flow (SQLite → Excel / CSV)

When Maria — or any user — uploads a .sqlite file:

Loading: The binary file is loaded into memory using FileReader, then passed to sql.js.
Initialization: A SQLite database is created in memory using WebAssembly.
Exploration: The user selects a table from a dropdown populated via SELECT name FROM sqlite_master.
Preview: The tool queries the table with SELECT * FROM table LIMIT 100 and shows a preview.
Export converted data:

CSV: Uses PapaParse to generate comma-separated text and create a Blob for download.
XLSX: Uses SheetJS to create a workbook, populate it with rows, and export it via the browser.

All operations are instant and local.

The conversion flow CSV / Excel → SQLite executes in similar manner.

Maria’s quiet breakthrough

Maria didn’t become a programmer. She still doesn’t write code professionally. But she solved her problem. Not by using a prebuilt system, but by assembling her own solution — piece by piece, guided by curiosity, urgency, and AI.

Surely, her tool is not production grade, it lacks a lot of functionality:

Exports only one data table from file
No support for relational schema (foreign keys, joins).
Cannot handle extremely large datasets.
No advanced type handling (e.g., ISO date detection, ENUM constraints).
No persistent workspace or history of previous conversions.

Maria isn’t worried. She has a tool that works for her tasks. And while she still didn’t consider herself a developer, she shared the online converter for others who may find it useful too: SQLite ↔ Excel Converter (eb43.github.io/sqlite-converter.html).

https://www.free-counters.org