SyneHQ is engineered for both cloud-hosted SaaS and enterprise self-hosted deployments with the same core architecture and security model.
Core Components
System Architecture
Architecture at a glance (TANGENT LAKE)
Architecture at a glance (DASHBOARDS + CHAT)
Component Details
Query Engine written in Go
Query Engine written in Go
- Federated Analytics: Cross-database query execution (TangentLake -> DuckDB)
- Query Optimization: Automatic performance tuning
- Type System: Universal data type handling
- Memory Management: Efficient resource utilization
AI Layer
AI Layer
- Natural Language Processing: Converts questions to queries
- Schema Understanding: Analyzes database structure
- Context Management: Maintains conversation state
- Learning System: Improves with user interactions
Connector Framework
Connector Framework
- Universal Connectivity: 20+ database types supported
- Protocol Support: SQL, NoSQL, and API connections
- Authentication: Secure credential management
- Connection Pooling: Efficient resource sharing
Security Layer
Security Layer
- Zero Trust: No implicit trust assumptions
- Encryption: End-to-end data protection
- Access Control: Role-based permissions
- Audit Logging: Comprehensive activity tracking
Data Flow
Query Processing Pipeline
Query Processing Pipeline
- Natural Language Input: User asks question in plain English
- AI Processing: Language model converts to query intent
- Schema Analysis: AI understands database structure
- Query Generation: SQL/NoSQL query created
- Execution: Query runs against target database
- Result Processing: Data formatted and visualized
- Response: Results returned to user
Security Flow
Security Flow
- Authentication: User credentials verified
- Authorization: Permissions checked for data access
- Query Validation: Query analyzed for security risks
- Execution: Query runs in user’s environment
- Audit Logging: All activities recorded
- Response: Results encrypted and returned
Scalability Features
Horizontal Scaling
- Load Balancing: Intelligent query distribution
- Multi-Instance: Support for multiple SyneHQ instances
- Database Sharding: Automatic query routing
- Resource Management: Dynamic resource allocation
Performance Optimization
- Query Caching: Intelligent result caching
- Connection Pooling: Efficient database connections
- Memory Management: Optimized memory usage
- Index Recommendations: Database optimization guidance
Technology Stack
Core Technologies
Infrastructure
- Containerization: Docker for deployment
- Orchestration: Kubernetes support
- Monitoring: Prometheus and Grafana
- Logging: Structured logging with ELK stack
Enterprise Features
Multi-Tenancy
High Availability
Compliance & Security
Deployment Guide
Learn how to deploy SyneHQ in your environment
Performance Tuning
Optimize SyneHQ for your workload
Security Configuration
Configure security settings and compliance