SQLite Litestream Tech Conference 2026

SQLite Litestream Conference

SQLite Litestream Tech Conference Edge Database WASM Turso LiteFS libSQL Distributed Cloudflare D1 Fly.io Replication Backup S3 Real-time

Modern SQLite Stack

# === Modern SQLite Technologies ===

# Turso — Distributed SQLite
# npm install @libsql/client
#
# import { createClient } from '@libsql/client';
#
# const client = createClient({
#   url: 'libsql://my-db-user.turso.io',
#   authToken: process.env.TURSO_AUTH_TOKEN,
# });
#
# const result = await client.execute('SELECT * FROM users WHERE id = ?', [1]);
# console.log(result.rows);
#
# // Embedded Replica (local cache)
# const client = createClient({
#   url: 'file:local.db',
#   syncUrl: 'libsql://my-db-user.turso.io',
#   authToken: process.env.TURSO_AUTH_TOKEN,
#   syncInterval: 60,  // sync every 60s
# });

# LiteFS — Fly.io
# fly launch
# # litefs.yml
# fuse:
#   dir: "/litefs"
# data:
#   dir: "/var/lib/litefs"
# proxy:
#   addr: ":8080"
#   target: "localhost:3000"
#   db: "app.db"
#   passthrough:
#     - "*.css"
#     - "*.js"
# lease:
#   type: "consul"
#   advertise-url: "http://.vm..internal:20202"
#   consul:
#     url: ""
#     key: "litefs/"

# Cloudflare D1
# wrangler d1 create my-database
# wrangler d1 execute my-database --command "CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)"

from dataclasses import dataclass
from typing import List

@dataclass
class SQLiteTech:
    name: str
    company: str
    year: int
    stars: int
    feature: str
    status: str

technologies = [
    SQLiteTech("Litestream", "Ben Johnson", 2021, 10500, "S3 WAL Streaming", "Stable"),
    SQLiteTech("LiteFS", "Fly.io", 2022, 3800, "FUSE Replication", "Stable"),
    SQLiteTech("Turso", "ChiselStrike", 2023, 2500, "Distributed libSQL", "GA"),
    SQLiteTech("Cloudflare D1", "Cloudflare", 2023, 0, "Edge SQLite", "GA"),
    SQLiteTech("cr-sqlite", "Vulcan", 2023, 4200, "CRDT SQLite", "Beta"),
    SQLiteTech("sql.js", "sql.js", 2019, 12000, "WASM SQLite", "Stable"),
]

print("=== SQLite Ecosystem ===")
for t in technologies:
    print(f"  [{t.status}] {t.name} by {t.company} ({t.year})")
    print(f"    Feature: {t.feature} | Stars: {t.stars:,}")

Conference Topics

# === Tech Conference 2026 Topics ===

@dataclass
class ConferenceTalk:
    title: str
    speaker: str
    track: str
    duration_min: int
    key_takeaway: str

talks = [
    ConferenceTalk(
        "SQLite at the Edge: Scaling to Millions",
        "Ben Johnson", "Database", 45,
        "Litestream v2 supports multi-destination replication"),
    ConferenceTalk(
        "Building Global Apps with Turso",
        "Glauber Costa", "Database", 30,
        "libSQL extensions: vector search, full-text in SQLite"),
    ConferenceTalk(
        "LiteFS: Zero-downtime SQLite in Production",
        "Fly.io Team", "Infrastructure", 30,
        "LiteFS v2 supports cross-region write forwarding"),
    ConferenceTalk(
        "CRDT-based SQLite for Offline-first Apps",
        "Matt Wonlaw", "Database", 45,
        "cr-sqlite enables conflict-free replication"),
    ConferenceTalk(
        "SQLite in WASM: Database in Your Browser",
        "sql.js Team", "Frontend", 30,
        "Full SQLite running in browser with IndexedDB backend"),
    ConferenceTalk(
        "From PostgreSQL to SQLite: Migration Guide",
        "Community", "Migration", 45,
        "When and how to migrate from Postgres to SQLite"),
]

print("\n=== Conference Schedule ===")
for t in talks:
    print(f"  [{t.track}] {t.title} ({t.duration_min}min)")
    print(f"    Speaker: {t.speaker}")
    print(f"    Takeaway: {t.key_takeaway}")

# Trends
trends = {
    "Edge Database": "SQLite ที่ Edge แทน Remote Database ลด Latency",
    "Embedded Replicas": "Turso Embedded Replica cache ที่ App Server",
    "CRDT Sync": "cr-sqlite ทำ Offline-first Sync ไม่ Conflict",
    "WASM": "SQLite ใน Browser ไม่ต้อง Backend สำหรับบาง Use Case",
    "Vector Search": "libSQL เพิ่ม Vector Search สำหรับ AI/ML",
    "Multi-region": "LiteFS + Turso ทำ Global Distribution",
}

print(f"\n=== 2026 Trends ===")
for trend, desc in trends.items():
    print(f"  [{trend}]: {desc}")

Migration และ Best Practices

# === SQLite Production Best Practices ===

# Performance Tuning
# PRAGMA journal_mode = WAL;          -- Write-Ahead Logging
# PRAGMA synchronous = NORMAL;         -- Faster writes
# PRAGMA cache_size = -64000;          -- 64MB cache
# PRAGMA foreign_keys = ON;            -- Enforce FK
# PRAGMA busy_timeout = 5000;          -- 5s wait on lock
# PRAGMA wal_autocheckpoint = 1000;    -- Checkpoint every 1000 pages
# PRAGMA mmap_size = 268435456;        -- 256MB memory-mapped I/O
# PRAGMA temp_store = MEMORY;          -- Temp tables in memory

# Python — Production SQLite Setup
# import sqlite3
#
# def get_db():
#     db = sqlite3.connect('app.db')
#     db.execute("PRAGMA journal_mode=WAL")
#     db.execute("PRAGMA synchronous=NORMAL")
#     db.execute("PRAGMA cache_size=-64000")
#     db.execute("PRAGMA busy_timeout=5000")
#     db.execute("PRAGMA mmap_size=268435456")
#     db.row_factory = sqlite3.Row
#     return db

# When to use SQLite vs PostgreSQL
decision_matrix = {
    "Single Server App": {"sqlite": "Perfect", "postgres": "Overkill"},
    "Mobile/Desktop App": {"sqlite": "Perfect", "postgres": "Not suitable"},
    "Edge/Serverless": {"sqlite": "Great (D1/Turso)", "postgres": "Possible"},
    "Multi-writer (>10 writes/s)": {"sqlite": "Not ideal", "postgres": "Perfect"},
    "Complex Queries": {"sqlite": "Good", "postgres": "Better"},
    "Full-text Search": {"sqlite": "FTS5 (good)", "postgres": "tsvector (great)"},
    "JSON Operations": {"sqlite": "Basic", "postgres": "JSONB (excellent)"},
    "Replication": {"sqlite": "Litestream/LiteFS", "postgres": "Built-in"},
}

print("Decision Matrix:")
print(f"  {'Use Case':<35} {'SQLite':<20} {'PostgreSQL'}")
for case, db in decision_matrix.items():
    print(f"  {case:<35} {db['sqlite']:<20} {db['postgres']}")

# Benchmark
benchmarks = {
    "Single Read": {"sqlite": "0.01ms", "postgres": "0.5ms"},
    "Batch Insert (10K)": {"sqlite": "50ms", "postgres": "200ms"},
    "Complex Join": {"sqlite": "15ms", "postgres": "8ms"},
    "Concurrent Reads (100)": {"sqlite": "0.02ms", "postgres": "1ms"},
    "Concurrent Writes (100)": {"sqlite": "500ms (serial)", "postgres": "50ms"},
}

print(f"\n\nBenchmark Comparison:")
for op, times in benchmarks.items():
    print(f"  {op}: SQLite {times['sqlite']} vs Postgres {times['postgres']}")

เคล็ดลับ

• WAL: เปิด WAL Mode เสมอสำหรับ Production
• Litestream: ใช้ Litestream สำหรับ Backup แบบ Real-time
• Turso: ใช้ Embedded Replica สำหรับ Low Latency Read
• PRAGMA: ตั้ง PRAGMA ที่เหมาะสมเพิ่ม Performance 10x
• Backup: ทดสอบ Restore เป็นประจำ

Best Practices สำหรับนักพัฒนา

การเขียนโค้ดที่ดีไม่ใช่แค่ทำให้โปรแกรมทำงานได้ แต่ต้องเขียนให้อ่านง่าย ดูแลรักษาง่าย และ Scale ได้ หลัก SOLID Principles เป็นพื้นฐานสำคัญที่นักพัฒนาทุกู้คืนควรเข้าใจ ได้แก่ Single Responsibility ที่แต่ละ Class ทำหน้าที่เดียว Open-Closed ที่เปิดให้ขยายแต่ปิดการแก้ไข Liskov Substitution ที่ Subclass ต้องใช้แทน Parent ได้ Interface Segregation ที่แยก Interface ให้เล็ก และ Dependency Inversion ที่พึ่งพา Abstraction ไม่ใช่ Implementation

เรื่อง Testing ก็ขาดไม่ได้ ควรเขียน Unit Test ครอบคลุมอย่างน้อย 80% ของ Code Base ใช้ Integration Test ทดสอบการทำงานร่วมกันของ Module ต่างๆ และ E2E Test สำหรับ Critical User Flow เครื่องมือยอดนิยมเช่น Jest, Pytest, JUnit ช่วยให้การเขียน Test เป็นเรื่องง่าย

เรื่อง Version Control ด้วย Git ใช้ Branch Strategy ที่เหมาะกับทีม เช่น Git Flow สำหรับโปรเจคใหญ่ หรือ Trunk-Based Development สำหรับทีมที่ Deploy บ่อย ทำ Code Review ทุก Pull Request และใช้ CI/CD Pipeline ทำ Automated Testing และ Deployment

สรุป

SQLite Litestream Tech Conference Edge Database WASM Turso libSQL LiteFS Cloudflare D1 Distributed Replication WAL PRAGMA Production Embedded Replica cr-sqlite CRDT