Stoolap Documentation

Welcome to the Stoolap Documentation! This is your comprehensive guide to using and understanding Stoolap, a high-performance HTAP database written in pure Go.

What is Stoolap?

Stoolap is a Hybrid Transactional/Analytical Processing (HTAP) database engine that combines transactional (OLTP) and analytical (OLAP) capabilities in a single system. Built entirely in Go with zero external dependencies, Stoolap features a row-based version store for efficient OLTP operations and columnar indexing for optimized analytical queries, providing a unified solution for diverse workloads.

Key Documentation Sections

Getting Started

Installation Guide - How to install and set up Stoolap
Quick Start Tutorial - A step-by-step guide to your first Stoolap database
Connection String Reference - Understanding and using Stoolap connection strings
API Reference - Complete API documentation for the Stoolap package

SQL Reference

Data Types - All supported data types and their behaviors
SQL Commands - SQL syntax and command reference
Aggregate Functions - Functions for data summarization
Scalar Functions - Built-in scalar functions
Window Functions - Row-based analytical functions
Temporal Queries (AS OF) - Time travel queries with AS OF syntax
CAST Operations - Type conversion capabilities
NULL Handling - Working with NULL values
JOIN Operations - Combining data from multiple tables
DISTINCT Operations - Working with unique values
Parameter Binding - Using parameters in SQL
Subqueries - Using queries within queries
Common Table Expressions (CTEs) - WITH clause for named subqueries

Architecture

Storage Engine - How data is stored and retrieved
Hybrid Storage - Row-based storage with columnar indexing
MVCC Implementation - Multi-Version Concurrency Control details
Transaction Isolation - Transaction isolation levels
Indexing - How indexes work and when to use them
Unique Indexes - Enforcing data uniqueness
Expression Pushdown - Filtering optimization

Performance

Query Execution - Understanding query execution
Vectorized Execution - SIMD-accelerated query processing
Data Compression - Storage compression techniques
Optimization - Query optimization strategies

Advanced Features

JSON Support - Working with JSON data
PRAGMA Commands - Database configuration options
Date/Time Handling - Working with temporal data
ON DUPLICATE KEY UPDATE - Handling duplicate key conflicts

Need Help?

If you can't find what you're looking for in the documentation, you can:

Open an issue on GitHub
Join the discussions to ask questions

This documentation is under active development. Contributions are welcome!