SQLite isn't just for mobile apps and prototypes anymore. Turso takes SQLite and turns it into a globally distributed, edge-native database platform that can run millions of databases simultaneously. Their database-per-tenant model is perfect for SaaS, embedded replicas enable offline-first apps, and they've added vector search for AI workloads. It's the database architecture you'd design if you were starting from scratch in 2026.

Main Features

• SQLite-Compatible Platform: Based on libSQL, an open-source SQLite fork with extended capabilities. Familiar SQL with modern distributed features on top.
• Edge-Native Architecture: Automatic multi-region replication puts data close to users. Sub-millisecond reads at the edge without complex database clustering.
• Embedded Replicas: Run replicas on the client device for local-first, offline-capable applications. Syncs with the server when connectivity returns.
• Database-Per-Tenant Model: Isolate customer data at the database level for SaaS multi-tenancy. Scale to millions of databases with per-tenant resource allocation.
• Point-in-Time Recovery: Scheduled backups with point-in-time recovery. Restore individual databases or entire organizations to any moment.
• Vector Search: Built-in vector search capabilities for AI and semantic applications. Store embeddings alongside your relational data.
• CLI-First Experience: Intuitive command-line interface for database management. Create, replicate, and manage databases from your terminal.
• Generous Free Tier: Free tier with substantial limits for prototyping, side projects, and indie development. Scale up when you need to without switching platforms.

Who Should Use It?

• SaaS Developers: Developers implementing multi-tenant database isolation at scale with a database-per-customer architecture.
• Edge Computing Engineers: Engineers needing low-latency data access at the edge with automatic multi-region distribution.
• Mobile Developers: App developers building offline-first experiences with embedded replicas that sync seamlessly.
• AI Developers: Engineers adding vector search to agent workflows and AI applications without a separate vector database.
• Startup CTOs: Technology leaders looking for cost-effective database scaling that starts free and grows predictably.
• Game Developers: Game teams needing lightweight embedded databases for game state, player data, and offline support.
• IoT Developers: Engineers managing device-level data stores with syncing, replication, and centralized querying.