OnlyAutomator’s data management system provides robust storage, processing, and analysis capabilities for content creator data. Data Architecture Overview

Data Categories

OnlyAutomator manages several categories of data:

1. User Data

Information about system users (content creators):
  • Account Information: Email, name, profile details
  • Authentication Details: Hashed passwords, session tokens
  • Preferences: System settings and preferences
  • Subscription Status: Current plan, billing information

2. Creator Analytics

Performance metrics for content creators:
  • Subscriber Metrics: Growth, churn, and engagement statistics
  • Revenue Data: Income streams, transaction history
  • Content Performance: Engagement with various content types
  • Message Analytics: Response times, engagement rates

3. Operational Data

System operational information:
  • System Logs: Application events and errors
  • Audit Trails: Record of significant user actions
  • Performance Metrics: System response times and health
  • Task Queue Status: Status of background processing jobs

Data Storage Solutions

The system uses multiple storage solutions optimized for different data types:

PostgreSQL (Supabase)

Primary relational database for structured data:
  • User accounts and profiles
  • Subscription and billing records
  • Creator analytics metrics
  • System configuration

Object Storage

Binary and large object storage:
  • User avatars and images
  • Exported reports and data files
  • System backups
  • Temporary processing files

Redis Cache

In-memory cache for high-speed data access:
  • Session data
  • Frequently accessed metrics
  • API response caching
  • Rate limiting information

Data Processing

OnlyAutomator implements several data processing mechanisms:

Real-time Processing

Immediate data handling for user-facing features:
  • Analytics dashboard updates
  • Notification generation
  • User action responses

Batch Processing

Scheduled tasks for intensive operations:
  • Daily analytics aggregation
  • Report generation
  • System maintenance
  • Data archiving

Event-driven Processing

Processing triggered by specific events:
  • Webhook responses
  • Subscription changes
  • External API updates
  • System alerts

Data Security

Comprehensive security measures protect all data:

Encryption

Multiple encryption layers:
  • Data at rest: All stored data encrypted
  • Data in transit: TLS/SSL for all communications
  • Field-level encryption: Extra protection for sensitive data
  • Encryption key management: Secure key rotation and storage

Access Control

Robust permissions system:
  • Role-based access: Appropriate permissions per user type
  • Row-level security: Data access limited to owners and authorized users
  • API authentication: Secure token-based API access
  • Admin audit logs: Tracking of all administrative actions

Compliance Features

Tools to meet regulatory requirements:
  • Data export: Complete data export for user requests
  • Data deletion: Comprehensive removal capabilities
  • Privacy controls: Granular user consent management
  • Retention policies: Configurable data retention periods

Data Integration

The system connects with multiple data sources:

OnlyFans Integration

Primary data source integration:
  • Credential management: Secure storage of access tokens
  • Data synchronization: Regular updates from OnlyFans API/scraping
  • Change detection: Identification of significant changes
  • Error handling: Robust handling of API changes and limitations

Third-party Sources

Additional integrations for enhanced functionality:
  • Payment processors: Transaction data from Stripe, PayPal
  • Marketing platforms: Campaign data from email and ad services
  • Social media: Basic metrics from connected social accounts
  • Analytics services: Enhanced metrics from Google Analytics, etc.

Data Governance

Policies ensuring proper data management:

Data Quality

Ensuring accurate and reliable data:
  • Validation rules: Data format and content verification
  • Consistency checks: Cross-reference verification
  • Error correction: Automated and manual correction workflows
  • Data completeness: Identification of missing information

Lifecycle Management

Managing data throughout its lifetime:
  • Creation policies: Standards for data entry and generation
  • Retention rules: Time-based data preservation policies
  • Archiving procedures: Moving older data to long-term storage
  • Deletion workflows: Secure data removal when appropriate

Disaster Recovery

Ensuring data survivability:
  • Regular backups: Automated daily and weekly backups
  • Point-in-time recovery: Ability to restore to specific moments
  • Geographic redundancy: Data stored in multiple physical locations
  • Recovery testing: Regular validation of restoration procedures