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Rust's memory safety and thread safety provide inherent security advantages, making it ideal for regulated industries like finance.
SurrealDB's Rust foundation ensures the highest levels of security and performance for financial applications where reliability is non-negotiable.
Integrated vector search and knowledge graph capabilities power conversational finance assistants, predictive analytics, and intelligent portfolio recommendations.
Relational, graph, time-series, and vector capabilities in a single AI-ready platform with enterprise-grade performance and flexible data modelling.
SEE IT IN ACTION
Use SurrealQL to traverse transaction graphs and uncover suspicious patterns across entities in a single query.
USE CASES
Graph data modelling to detect suspicious patterns, anomalous transactions, and hidden connections for KYC link analysis and identity fraud detection.
Time-series data for tick-by-tick market feeds, historical performance tracking, portfolio risk metrics, and algorithmic trading strategy backtesting.
Historical and time travel querying for auditing previous data states, meeting regulatory requirements, and governance.
Applications that reason across financial knowledge using vector embeddings, structured data, and semantic relationships.
Power mobile banking apps, trading dashboards, and compliance alerts with a single operational data layer.
Generative document processing for contracts, reports, filings, and automated customer service chatbots.
TRUSTED BY
Samsung uses SurrealDB to power knowledge graphs for real-time audience insights and ad targeting in its ad division.
Learn moreTencent uses SurrealDB to consolidate nine backend tools into one real-time monitoring platform.
Learn moreWHY SURREALDB
Scale effortlessly as your customer base and transaction volume grow - no complex sharding required.
Start schemaless, then add structure as needed to adapt to evolving financial products and regulatory fields.
Power trading dashboards and compliance alerts with a single operational data layer for immediate financial intelligence.
Built-in historical querying and audit capabilities meet regulatory requirements without additional infrastructure.
Built-in vector search and knowledge graph capabilities enable next-generation fintech applications.