Building a SQL-like Relational Database Engine in C++ From Scratch

The article describes Ark, a SQL-like relational database engine built entirely from scratch in C++ by developer Devansh Kashyap, with the goal of learning database internals rather than competing with production systems. The engine supports core SQL features including aggregate functions, filtering, joins, schema evolution via ALTER TABLE, and persistence, all implemented manually without external libraries or parser generators. The project is structured as a modular pipeline of tokenizer, parser, command objects, execution engine, storage layer, and persistence, with the source code available on GitHub for feedback.

Most of us use databases every day. But at some point I started wondering: SELECT statement?So instead of only reading about databases, I decided to build one. That project became Ark — a SQL-like relational database engine written entirely from scratch in C++. I wanted to understand the internals of database systems by implementing the pieces myself instead of relying on existing engines or parser generators. The goal wasn’t to compete with production databases. The goal was to learn: Ark currently supports: COUNT , SUM , AVG , MIN , MAX ALTER TABLE LIKE pattern matchingORDER BY DISTINCT SAVE / LOAD Everything is manually implemented. No external database libraries. No parser generators. No embedded SQL engines. The execution pipeline looks roughly like this: Query ↓ Tokenizer ↓ Parser ↓ Command Objects ↓ Execution Engine ↓ Storage Layer ↓ Persistence The project is split into modular components: CREATE TABLE employees id INT, name STRING, salary DOUBLE ; INSERT INTO employees VALUES 1, "Alice", 95000.0 , 2, "Bob", 72000.0 ; SELECT FROM employees WHERE salary 80000.0; One of the most interesting challenges was implementing joins and schema evolution. Handling: ALTER TABLE became much more complicated than I initially expected. Parser correctness and diagnostics also took a surprising amount of effort. Building Ark taught me a lot about: It also gave me a much deeper appreciation for real database engines. GitHub Repository: https://github.com/kashyap-devansh/Ark I’d genuinely appreciate feedback from people interested in: Especially suggestions for improving the architecture or query engine.