Building a Database Engine from Scratch

Introduction to Database Engines

Database engines are complex systems that manage data storage, retrieval, and manipulation. In this tutorial, we'll build a simple but functional database engine to understand the core concepts.

Core Components

• Storage Engine - Managing data on disk
• Buffer Manager - Caching frequently accessed data
• Index Manager - Efficient data lookup
• Query Processor - Executing queries

Basic Storage Engine Implementation

package main

import (
    "os"
    "encoding/binary"
)

type Page struct {
    id       uint64
    data     []byte
    isDirty  bool
}

type StorageEngine struct {
    filename string
    pageSize int
    pages    map[uint64]*Page
}

func NewStorageEngine(filename string, pageSize int) *StorageEngine {
    return &StorageEngine{
        filename: filename,
        pageSize: pageSize,
        pages:    make(map[uint64]*Page),
    }
}

func (se *StorageEngine) ReadPage(pageID uint64) (*Page, error) {
    // Implementation details...
}

func (se *StorageEngine) WritePage(page *Page) error {
    // Implementation details...
}
                

Implementing B-Tree Indexing

B-Trees are the most common indexing structure in databases. Let's implement a basic B-Tree:

type BTreeNode struct {
    isLeaf    bool
    keys      []int
    children  []*BTreeNode
    data      [][]byte
}

type BTree struct {
    root     *BTreeNode
    degree   int
}

func (t *BTree) Insert(key int, data []byte) {
    // Implementation details...
}

func (t *BTree) Search(key int) ([]byte, bool) {
    // Implementation details...
}
                

Query Processing

A query processor takes SQL queries and executes them efficiently. Here's a simple implementation:

type QueryProcessor struct {
    storage *StorageEngine
    index   *BTree
}

func (qp *QueryProcessor) ExecuteQuery(query string) (Result, error) {
    // Parse query
    // Plan execution
    // Execute plan
    // Return results
}
                

Performance Considerations

When building a database engine, several performance aspects need consideration:

• Disk I/O optimization
• Memory management
• Concurrency control
• Query optimization

Next Steps

This implementation can be extended with:

• Transaction support
• ACID properties
• Advanced indexing structures
• Query optimization