damjan_savicandClaude Opus 4.5
43484c5023
- Add 100 blog posts covering AI, development, and tech topics - Add .env.example for environment configuration - Add accessibility and lighthouse audit scripts - Remove obsolete SEO reports and temporary files - Remove dev-dist build artifacts and backup files - Remove unused portrait images (moved/consolidated elsewhere) - Update contact form and component improvements Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
451 lines
12 KiB
Markdown
451 lines
12 KiB
Markdown
# Turso & libSQL: SQLite für die Edge
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**Meta-Description:** Turso als Edge-Hosted SQLite mit libSQL. Embedded Replicas, Vector Search und Local-First Development.
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**Keywords:** Turso, libSQL, SQLite Edge, Embedded Replicas, Local-First, Edge Database, Distributed SQLite
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---
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## Einführung
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Turso bringt **SQLite in die Edge**. Basierend auf libSQL (einem SQLite-Fork) bietet es embedded Replicas, globale Verteilung und native Vector Search – perfekt für Low-Latency Anwendungen weltweit.
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---
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## Turso Architecture
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```
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┌─────────────────────────────────────────────────────────────┐
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│ TURSO ARCHITECTURE │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ Primary Database (Write): │
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│ └── Zentraler Write-Node │
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│ │
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│ Edge Replicas (Read): │
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│ ├── Frankfurt │
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│ ├── New York │
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│ ├── Singapore │
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│ └── São Paulo │
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│ └── Automatische Synchronisation │
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│ │
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│ Embedded Replicas (On-Device): │
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│ ├── In-App SQLite Kopie │
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│ ├── Offline-fähig │
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│ └── Sync bei Reconnect │
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│ │
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│ Features: │
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│ ├── libSQL (SQLite Fork) │
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│ ├── Native Vector Search │
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│ ├── Branching (wie Git) │
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│ └── MCP Server für AI Assistants │
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│ │
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└─────────────────────────────────────────────────────────────┘
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```
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---
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## Setup
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```bash
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# Turso CLI installieren
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curl -sSfL https://get.tur.so/install.sh | bash
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# Login
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turso auth login
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# Database erstellen
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turso db create my-app --location fra # Frankfurt
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# Replicas hinzufügen
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turso db replicas add my-app --location iad # US East
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turso db replicas add my-app --location sin # Singapore
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# Connection URL und Token
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turso db show my-app --url
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turso db tokens create my-app
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```
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```bash
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# Node.js Client installieren
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npm install @libsql/client
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```
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---
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## Basic Connection
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```typescript
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// lib/turso.ts
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import { createClient } from '@libsql/client';
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export const turso = createClient({
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url: process.env.TURSO_DATABASE_URL!,
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authToken: process.env.TURSO_AUTH_TOKEN!
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});
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// Für lokale Entwicklung (SQLite File)
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export const localDb = createClient({
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url: 'file:local.db'
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});
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```
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---
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## CRUD Operations
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```typescript
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import { turso } from '@/lib/turso';
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// CREATE TABLE
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async function initializeSchema() {
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await turso.execute(`
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CREATE TABLE IF NOT EXISTS users (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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email TEXT UNIQUE NOT NULL,
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name TEXT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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)
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`);
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await turso.execute(`
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CREATE TABLE IF NOT EXISTS posts (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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title TEXT NOT NULL,
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content TEXT,
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author_id INTEGER NOT NULL,
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published INTEGER DEFAULT 0,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (author_id) REFERENCES users(id)
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)
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`);
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}
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// CREATE
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async function createUser(email: string, name: string) {
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const result = await turso.execute({
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sql: 'INSERT INTO users (email, name) VALUES (?, ?) RETURNING *',
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args: [email, name]
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});
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return result.rows[0];
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}
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// READ
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async function getUserById(id: number) {
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const result = await turso.execute({
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sql: 'SELECT * FROM users WHERE id = ?',
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args: [id]
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});
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return result.rows[0];
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}
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async function getPostsWithAuthors() {
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const result = await turso.execute(`
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SELECT
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p.id,
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p.title,
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p.content,
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p.created_at,
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u.name as author_name,
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u.email as author_email
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FROM posts p
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JOIN users u ON p.author_id = u.id
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WHERE p.published = 1
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ORDER BY p.created_at DESC
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`);
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return result.rows;
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}
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// UPDATE
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async function updatePost(id: number, title: string, content: string) {
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const result = await turso.execute({
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sql: 'UPDATE posts SET title = ?, content = ? WHERE id = ? RETURNING *',
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args: [title, content, id]
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});
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return result.rows[0];
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}
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// DELETE
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async function deletePost(id: number) {
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await turso.execute({
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sql: 'DELETE FROM posts WHERE id = ?',
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args: [id]
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});
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}
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// BATCH (Transaction)
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async function createUserWithPosts(
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user: { email: string; name: string },
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posts: { title: string; content: string }[]
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) {
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const result = await turso.batch([
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{
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sql: 'INSERT INTO users (email, name) VALUES (?, ?) RETURNING id',
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args: [user.email, user.name]
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},
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...posts.map(post => ({
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sql: 'INSERT INTO posts (title, content, author_id) VALUES (?, ?, last_insert_rowid())',
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args: [post.title, post.content]
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}))
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], 'write');
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return result;
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}
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```
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---
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## Embedded Replicas (Local-First)
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```typescript
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// lib/turso-embedded.ts
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import { createClient } from '@libsql/client';
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// Embedded Replica mit Sync
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export const db = createClient({
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url: 'file:local-replica.db', // Lokale SQLite Datei
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syncUrl: process.env.TURSO_DATABASE_URL!,
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authToken: process.env.TURSO_AUTH_TOKEN!,
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syncInterval: 60 // Sync alle 60 Sekunden
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});
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// Manuelle Synchronisation
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async function syncDatabase() {
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await db.sync();
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console.log('Database synced with remote');
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}
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// Verwendung
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async function getDataWithFallback() {
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try {
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// Versuche lokale Query (schnell!)
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const result = await db.execute('SELECT * FROM posts LIMIT 10');
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return result.rows;
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} catch (error) {
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// Fallback zu Remote bei Fehler
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await db.sync();
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const result = await db.execute('SELECT * FROM posts LIMIT 10');
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return result.rows;
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}
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}
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```
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---
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## Vector Search
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```typescript
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// libSQL unterstützt native Vector Operations
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// Tabelle mit Vector Column
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await turso.execute(`
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CREATE TABLE IF NOT EXISTS documents (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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content TEXT NOT NULL,
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embedding F32_BLOB(1536), -- OpenAI ada-002 Dimension
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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)
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`);
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// Vector Index erstellen
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await turso.execute(`
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CREATE INDEX IF NOT EXISTS documents_embedding_idx
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ON documents (libsql_vector_idx(embedding))
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`);
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// Document mit Embedding speichern
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async function saveDocument(content: string, embedding: number[]) {
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await turso.execute({
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sql: `
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INSERT INTO documents (content, embedding)
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VALUES (?, vector32(?))
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`,
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args: [content, JSON.stringify(embedding)]
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});
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}
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// Similarity Search
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async function searchSimilar(queryEmbedding: number[], limit: number = 5) {
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const result = await turso.execute({
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sql: `
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SELECT
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id,
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content,
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vector_distance_cos(embedding, vector32(?)) as distance
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FROM documents
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ORDER BY distance ASC
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LIMIT ?
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`,
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args: [JSON.stringify(queryEmbedding), limit]
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});
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return result.rows.map(row => ({
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id: row.id,
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content: row.content,
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similarity: 1 - (row.distance as number) // Convert distance to similarity
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}));
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}
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```
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---
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## Drizzle ORM Integration
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```typescript
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// drizzle.config.ts
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import { defineConfig } from 'drizzle-kit';
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export default defineConfig({
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schema: './src/db/schema.ts',
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out: './drizzle',
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dialect: 'turso',
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dbCredentials: {
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url: process.env.TURSO_DATABASE_URL!,
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authToken: process.env.TURSO_AUTH_TOKEN!
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}
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});
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```
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```typescript
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// src/db/schema.ts
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import { sqliteTable, text, integer } from 'drizzle-orm/sqlite-core';
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export const users = sqliteTable('users', {
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id: integer('id').primaryKey({ autoIncrement: true }),
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email: text('email').notNull().unique(),
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name: text('name'),
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createdAt: integer('created_at', { mode: 'timestamp' })
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.notNull()
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.$defaultFn(() => new Date())
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});
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export const posts = sqliteTable('posts', {
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id: integer('id').primaryKey({ autoIncrement: true }),
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title: text('title').notNull(),
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content: text('content'),
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authorId: integer('author_id')
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.notNull()
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.references(() => users.id),
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published: integer('published', { mode: 'boolean' }).default(false),
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createdAt: integer('created_at', { mode: 'timestamp' })
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.notNull()
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.$defaultFn(() => new Date())
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});
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```
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```typescript
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// src/db/index.ts
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import { drizzle } from 'drizzle-orm/libsql';
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import { createClient } from '@libsql/client';
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import * as schema from './schema';
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const client = createClient({
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url: process.env.TURSO_DATABASE_URL!,
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authToken: process.env.TURSO_AUTH_TOKEN!
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});
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export const db = drizzle(client, { schema });
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// Queries
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import { eq } from 'drizzle-orm';
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async function getUserWithPosts(userId: number) {
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return await db.query.users.findFirst({
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where: eq(users.id, userId),
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with: {
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posts: true
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}
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});
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}
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```
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---
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## Database Branching
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```bash
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# Branch erstellen (wie Git)
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turso db branch create my-app feature-branch
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# Branch verwenden
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turso db show my-app/feature-branch --url
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# Branch mergen (manuell - Schema migrieren)
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turso db branch delete my-app feature-branch
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```
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```typescript
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// Branch in Code verwenden
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const branchDb = createClient({
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url: process.env.TURSO_BRANCH_URL!, // Feature Branch URL
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authToken: process.env.TURSO_AUTH_TOKEN!
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});
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// Schema-Änderungen testen
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await branchDb.execute(`
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ALTER TABLE users ADD COLUMN avatar_url TEXT
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`);
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// Nach Test: Änderungen auf Production anwenden
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```
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---
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## Edge Functions Integration
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```typescript
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// Cloudflare Workers
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export default {
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async fetch(request: Request, env: Env) {
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const db = createClient({
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url: env.TURSO_DATABASE_URL,
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authToken: env.TURSO_AUTH_TOKEN
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});
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const { pathname } = new URL(request.url);
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if (pathname === '/api/posts') {
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const result = await db.execute(
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'SELECT * FROM posts WHERE published = 1 ORDER BY created_at DESC LIMIT 10'
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);
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return new Response(JSON.stringify(result.rows), {
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headers: { 'Content-Type': 'application/json' }
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});
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}
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return new Response('Not Found', { status: 404 });
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}
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};
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```
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---
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## Fazit
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Turso bietet:
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1. **Global Edge Distribution**: Replicas weltweit für Low-Latency
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2. **Embedded Replicas**: Local-First mit automatischem Sync
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3. **SQLite Compatibility**: Bewährte Technologie, moderne Distribution
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4. **Native Vector Search**: AI-ready ohne externe Services
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Ideal für globale Anwendungen mit Offline-Support.
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---
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## Bildprompts
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1. "Globe with database nodes connected at edge locations, global distribution"
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2. "SQLite file syncing between device and cloud, embedded replica concept"
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3. "Local-first application working offline then syncing, connectivity visualization"
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---
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## Quellen
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- [Turso Documentation](https://docs.turso.tech/)
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- [libSQL GitHub](https://github.com/tursodatabase/libsql)
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- [Turso Embedded Replicas](https://turso.tech/blog/local-first-cloud-connected-sqlite-with-turso-embedded-replicas)
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- [Turso Vector Search](https://docs.turso.tech/features/vector-search)
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