CAPABILITIES
Built with granular security, by default
Memory-safe, security-first language
Built in Rust to protect PHI and meet stringent regulatory demands such as GDPR. Ships effortlessly to browsers (WASM), wearables, and bedside IoT gateways.
Runs everywhere - embedded, in-browser, on the edge
Keep latency-sensitive AI inference close to the patient. Perfect for rural telehealth kits that store data locally and sync when connectivity returns.
Unified OLTP / BaaS architecture
Real-time ingest and API server in one component. Mobile nursing apps can write vitals, schedule medication, and trigger AI triage rules through the same endpoint.
Native vector search + knowledge graph
Store embeddings alongside structured patient data with graphs capturing complex biomedical relationships for generative AI clinical co-pilots.
SEE IT IN ACTION
Find similar patient cases with vector search
Combine structured EHR data with vector similarity to surface relevant diagnoses and treatment pathways.
USE CASES
Core use cases for healthcare
Precision medicine and clinical decision support
Fuse vector search with longitudinal EHR, genomics, and imaging data to surface differential diagnoses and personalised care pathways.
Edge-ready medical telemetry and IoT
Rust-built binaries run embedded or in-browser (WASM) so bedside monitors and wearables can ingest time-series vitals locally.
AI-enhanced imaging and diagnostics
Store embeddings for X-ray, CT or pathology slides alongside metadata. Native vector index retrieves visually similar cases.
Patient-facing chatbots
Knowledge graphs pull lab results, appointments, and literature into a single semantic layer for clinically grounded conversational agents.
Fraud detection and billing integrity
Embedded graph analytics traverse provider-patient-procedure networks in real time, flagging anomalous claim patterns.
Continuous remote monitoring
High-frequency sensor streams feed the time-series engine; anomaly detectors alert clinicians to arrhythmias or sepsis risk in sub-second latency.
TRUSTED BY
Powering innovation across industries
Unlocking insights with knowledge graphs
Samsung uses SurrealDB to power knowledge graphs 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 moreWHY SURREALDB
Why healthcare organisations choose SurrealDB
Horizontal scalability
Handle national health-service-scale datasets and hundreds of simultaneous AI agents without re-architecting.
Flexible and versatile data model
Switch between document, graph, and time-series views with one engine - ideal for evolving research schemas.
Graph queries for complex patterns
Detect multi-hop patterns for insurance fraud detection, care pathway optimisation, and zero-trust security graphs.
Time-series analytics
Sub-second aggregation over high-frequency sensor feeds for cardiac telemetry anomaly detection and risk-scoring wearables.
Historical querying with SurrealKV
Immutable time-travel queries simplify compliance audits, post-incident investigations, and pharmacovigilance back-testing.
