Beyond SQLite: AI, search,
and real-time in SurrealDB
Rust-powered. ML-ready. Build embedded apps that think, adapt, and scale.
Rust-powered. ML-ready. Build embedded apps that think, adapt, and scale.
SQLite wasn’t built for modern embedded intelligence. AI-driven sensors, offline vector search, and on-device inference expose its limitations.
SQLite added JSONB in 2023, 10 years after PostgreSQL.
No vector search, ML inference, or real-time updates.
Single-threaded C code struggles on multi-core hardware.
SurrealDB’s Rust-powered embedded engine. It’s SQLite-like in simplicity but built for performance, safety, and modern workloads.
Run ONNX models directly inside the database. Example: predict equipment failures using local telemetry.
SurrealDB supports vector and full-text search for AI/ML use cases (e.g., image similarity on a drone).
Blend relational, document, and graph data seamlessly. Example: combine vector results with structured business data.
Thread-safe, memory-efficient, and built for modern hardware.
Embed models, run inferences, and perform vector search without external services.
Start on a microcontroller and scale up to a distributed cluster.
Adapt to new use cases without additional databases.
Get started with SurrealDB: the embedded database for knowledge-intensive applications.
