The Fraud Database is an open-source community project by OpenAutonomyX (OPC) Private Limited, designed to empower cyber crime cells and their officers to investigate cyber crime cases more efficiently. It equips investigators with unified data infrastructure and AI-powered intelligence capabilities to accelerate detection, analysis, and response.
The Fraud Database (TFDB) is deployed as an open-source multi-model database built in Rust, engineered to unify multiple data models into a single, powerful engine.
It combines:
- Document
- Graph
- Time-series
- Relational
- Geospatial
- Key-value
data types into one unified query language with powerful search and retrieval capabilities (vector, full-text, and hybrid search), along with real-time and event-driven functionality. This enables developers and investigators to build high-performance applications faster and more efficiently.
Core Features
1. Native Multi-Model Architecture
TFDB combines document, graph, time-series, relational, geospatial, and key-value data models natively within a single query language — without workarounds or added complexity.
2. AI-Native Design
Purpose-built for AI and context-aware applications, TFDB integrates vector, full-text, and hybrid search. It blends semantic intelligence, graph relationships, and relational querying into one unified system.
3. Real-Time and Event-Driven
Built-in real-time subscriptions, event triggers, and streaming updates power reactive, real-time investigative workflows — without requiring additional layers such as external streaming platforms.
4. Powerful Developer Experience
The query language combines the best ideas from SQL, NoSQL, and graph paradigms within a single native syntax. Developers can start schemaless and progressively enforce strict schema definitions as needed.
5. Rust-Powered Performance
Built as a single Rust binary, TFDB delivers high efficiency, memory safety, type safety, and strong concurrency guarantees.
6. Strong Testing and Performance Coverage
Internal Rust testing frameworks validate thousands of database output assertions on every pull request. Performance benchmarking ensures each change maintains or improves system efficiency.
7. Native ACID Compliance
TFDB guarantees immediate data consistency through ACID compliance. Where required, it also supports eventual consistency models for specific distributed scenarios.
8. Flexible Deployment
The single Rust binary architecture supports multiple deployment models:
- Embedded (in-application)
- Browser-based via WebAssembly
- Traditional backend deployment
- Single-node setup
- Highly scalable distributed clusters
9. Secure by Design
Security is built-in by default, including:
- Role-Based Access Control (RBAC)
- Record-level permissions
- Fine-grained access controls
- JWT authentication
- Multi-tenant isolation
- Compliance alignment (SOC 2, ISO 27001)
Mission
The Fraud Database (TFDB) is an open-source community initiative by OpenAutonomyX (OPC) Private Limited with a clear mission:
To strengthen cyber crime investigation capabilities by equipping law enforcement agencies with advanced data infrastructure and AI-powered intelligence tools — enabling faster case resolution, deeper analysis, and proactive fraud prevention.Press. This is your first post. Edit or delete it, then start writing!