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Build intelligent embedded and edge applications

Q: Can SurrealDB run embedded inside my application?

Yes. SurrealDB can be embedded as a library directly in your Rust, JavaScript, or Python application. It runs in-process with no separate server, making it ideal for desktop apps, CLI tools, and resource-constrained devices.

Q: Does SurrealDB work offline?

Yes. SurrealDB stores data locally when embedded, so your application continues to work without connectivity. You can export and import data using standard SurrealDB tooling to move data between local and remote instances as needed.

Q: Can SurrealDB run in the browser?

Yes. SurrealDB compiles to WebAssembly (WASM) and runs entirely in the browser with the same query engine as the server. This enables offline-first web apps with local data storage and real-time querying on the client.

Q: What is the resource footprint of embedded SurrealDB?

SurrealDB is built in Rust and compiles to a single binary with no runtime dependencies. The memory and CPU footprint is minimal, making it suitable for IoT gateways, point-of-sale terminals, and other edge hardware.

Q: Is the query language the same in embedded and server modes?

Yes. SurrealQL works identically whether SurrealDB runs embedded, as a standalone server, or in SurrealDB Cloud. Your application code, schemas, and queries are fully portable across deployment modes.

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.

THE CHALLENGE

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.

THE SOLUTION

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

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

SurrealDB 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

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 centralised policies and audit trails.

TRUSTED BY

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.

Learn more

Frequently Asked Questions

Can SurrealDB run embedded inside my application?

Does SurrealDB work offline?

Can SurrealDB run in the browser?

What is the resource footprint of embedded SurrealDB?

Is the query language the same in embedded and server modes?

LET'S GOOOO

Ready to build embedded and edge systems?

Build dynamic, intelligent systems and enhance AI-driven data analysis, for real-time, actionable insights.

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