New

Vector RAG that actually understands context

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Build intelligent embedded and edge applications

SurrealDB brings multi-model database power to the edge - from vehicles and robotics to browsers and kiosks. Use the same engine in the cloud, embedded or in the edge.

Why traditional embedded databases fall short

Modern devices run high-performance LLMs locally, enabling private, low-latency, offline intelligence. These on-device systems need data layers that store embeddings, context, and evolving memory right on the device.

Lack of AI data types

Classic embedded stores were built for rows, not vectors, time-series, documents or relationships - far from the multi-model data AI relies on.

Schema and concurrency

LLMs shift schemas and update context constantly, overwhelming SQLite's rigid schemas and single-writer engines.

Edge and cloud sync

Edge AI systems are never just “one device forever”: you want cloud sync, multi-device state, sometimes federated learning or global analytics.

Limited built-in security

Edge devices handle sensitive data, but traditional stores lack native encryption, row-level security and fine-grained access control.

SurrealDB is the embedded database for edge-AI

Multi-model data in the edge

Handle structured data, context graphs, vector embeddings and sensor streams in a single edge database.

Flexible schema

As on-device agents learn and their data shapes change, SurrealDB accepts evolving schemas — no rigid tables, no migration pain.

Embedded runtime

The same engine runs as a lightweight Rust binary, WASM or cloud - ideal for embedded and edge devices with cloud sync.

Governance complexity

Managing access controls, audit trails, and compliance across multiple systems creates security gaps and operational burden.

One database. Any environment.

Run the same SurrealDB engine embedded in your app, at the edge, or in the cloud - without changing your data model or code.

Real-world scenarios

From industrial IoT to mobile field apps, SurrealDB powers edge applications across industries.

Retail point-of-sale resilience

Keep checkout lines moving when the store's WAN link is saturated.

Mobile field applications

Field technicians record inspections and photos in remote areas with offline-first functionality.

Connected vehicles

Vehicles stream telemetry, require local classification, and must pass compliance audits.

Security and governance built-in

Meet regulatory requirements without wrapping your DB in yet another proxy.

End-to-end encryption

Data at rest and in transit uses device-scoped keys. SurrealDB never exposes plaintext outside the node.

Fine-grained RBAC

Define permissions once in schema and reuse edge-to-cloud. Auditors trace every update with commit hashes.

Deterministic plugins

Surrealism runs in a sandboxed WebAssembly VM. Memory limits and capability filters prevent plugins from touching the OS.

Regulatory alignment

Keep PII local to comply with data residency, edge-redact before sync, or run homomorphic encryption plugins.

Business impact

Lower latency

Lower latency vs. cloud-only calls, improving UX and conversion rates.

Fewer components

Cut microservices count, caches, and message buses, slashing ops overhead.

Faster delivery

Developers iterate on schema and edge logic in a single repo; no hand-offs between teams.

Single governance

Unified governance model from edge to core with centralized policies and audit trails.

Powering innovation across industries

Unlocking insights with knowledge graphs

Samsung uses SurrealDB to power a knowledge graph for real-time audience insights and ad targeting in its ad division.

Learn more

Unified infrastructure monitoring

Tencent uses SurrealDB to consolidate nine backend tools into one real-time monitoring platform.