libSQL Technical Reference - AI-Optimized

Overview

libSQL is a SQLite fork that adds network capabilities and replication. Built by Turso in 2023 to address SQLite's closed development model and networking limitations.

Core Architecture

What It Is

• SQLite fork with identical file format and API compatibility
• Adds HTTP/WebSocket networking layer
• Implements embedded replicas for distributed reads
• Open source (MIT license) with managed service option

Key Differentiator

SQLite works only as embedded database. libSQL adds network access while maintaining SQLite's simplicity and performance characteristics.

Critical Features & Failure Modes

Embedded Replicas

Function: Local SQLite file syncs with remote database

• Reads: Microsecond latency (local file access)
• Writes: Background sync to remote server
• Sync interval: Configurable (default 60 seconds)

Critical Failure Modes:

• Sync failures are silent - data accumulates in local WAL without indication
• Conflict resolution: "last write wins" only - data loss possible
• Network interruptions create unresolved conflicts lasting hours
• No built-in conflict detection or resolution mechanisms

Production Configuration:

const db = createClient({
  url: "libsql://your-db.turso.io",
  authToken: "your-token", 
  syncUrl: "libsql://your-db.turso.io",
  syncInterval: 60, // Too low hammers API, too high delays sync
});

WebAssembly Functions

Capability: Custom database functions in any WASM-compatible language

Performance Impact:

• 2-5x slower than native SQLite functions
• Memory limits kill functions without warning
• No filesystem/network access (security sandbox)

Debugging Reality: Stack traces are useless, debugging is extremely difficult

Enhanced ALTER TABLE

Improvement: Full ALTER TABLE support vs SQLite's limited capabilities

• Can change column types, add constraints
• Recreates table behind scenes with proper handling

Breaking Change: Randomized ROWID breaks code relying on predictable row ordering

Performance Characteristics

Real-World Numbers

• Local reads: ~200 nanoseconds (embedded replica)
• Remote writes: <100ms typical, varies with network
• Global latency: ~50ms (Vercel benchmarks, best case)
• Cold start: Instant vs PostgreSQL's 3+ second wake-up

Performance Limitations

• Complex queries with JOINs over 100k+ rows hit SQLite query planner limits
• Concurrent writes limited to one writer per database (SQLite constraint)
• Transaction size limits cause timeouts on large imports
• Sync conflicts create 30+ second delays during resolution

Resource Requirements & Limits

Turso Managed Service Limits

• Free tier: 9GB storage, 500 databases
• Account limit: 500 databases maximum before enterprise pricing
• API request limits affect cost with small, frequent queries

Self-Hosting Requirements

• Docker deployment available
• Full feature parity with managed service
• Requires proper backup and monitoring setup

Decision Criteria

Use libSQL When:

• Need SQLite simplicity with network access
• Global read latency is critical (embedded replicas)
• Building offline-first mobile applications
• Want built-in vector search without extensions
• Small to medium scale with read-heavy workloads

Avoid libSQL When:

• Need strong consistency (conflict resolution is primitive)
• Require multiple concurrent writers
• Complex analytical queries are primary use case
• Mission-critical systems without tolerance for silent sync failures
• High-frequency write workloads (will overwhelm sync API)

Migration Risk Assessment

• Low Risk: Basic CRUD operations, existing SQLite files
• Medium Risk: Code depending on ROWID ordering, custom SQLite extensions
• High Risk: Systems requiring immediate consistency, complex replication needs

Critical Warnings

What Documentation Doesn't Tell You

1. Silent Sync Failures: No notification when replication breaks
2. Conflict Resolution: Only "last write wins" - no merge strategies
3. ROWID Changes: Randomization breaks ordering-dependent code
4. Vector Search: Performance degrades significantly at scale
5. WASM Functions: Production debugging is extremely difficult

Common Failure Scenarios

• Network interruptions during sync create data inconsistencies
• Large schema migrations can block database for extended periods
• Memory limits in WASM functions cause silent crashes
• API rate limits hit unexpectedly with small query patterns

Language Support Quality

Production Ready

• TypeScript/JavaScript: @libsql/client - mature, well-maintained
• Rust: Native support, optimal performance
• Go: go-libsql - decent stability

Limited Support

• Python: Experimental only, not production ready
• Other Languages: HTTP API compatibility varies, test thoroughly

Competitive Analysis

vs SQLite

• Advantage: Network access, replication, vector search
• Disadvantage: Additional complexity, sync failure risks

vs PostgreSQL

• Advantage: Simpler deployment, faster cold starts, embedded option
• Disadvantage: Single writer limitation, less mature ecosystem

vs Cloudflare D1

• Advantage: Self-hosting option, open source
• Disadvantage: Less global distribution, manual scaling

Implementation Intelligence

Successful Patterns

• Start with embedded replicas for read-heavy workloads
• Implement proper monitoring for sync status
• Use prepared statements for performance
• Design around eventual consistency model

Anti-Patterns

• Relying on immediate consistency across replicas
• Using WASM functions for performance-critical operations
• Ignoring sync failure monitoring
• Migrating complex PostgreSQL workloads directly

Testing Requirements

• Test sync failure scenarios extensively
• Validate conflict resolution behavior
• Benchmark performance with realistic data sizes
• Test offline/online transitions thoroughly

Monitoring & Operations

Critical Metrics

• Sync lag between local and remote
• Failed sync attempts and resolution time
• Query performance on embedded vs remote
• WASM function memory usage and crash rates

Operational Complexity

• Low: Basic CRUD with embedded replicas
• Medium: Custom WASM functions, complex schemas
• High: Multi-region deployments, conflict resolution

This summary provides the technical foundation for implementing libSQL while avoiding documented failure modes and leveraging operational intelligence from real-world usage.