The Inventory Read Model is a PostgreSQL database that serves as an optimized projection of inventory data for high-performance read operations. This read model is specifically designed to support fast queries for stock levels, product availability, and inventory reporting across our e-commerce platform.

Overview

This read model is maintained by the Inventory Service and provides denormalized views of inventory data that are optimized for query performance. It serves as the primary data source for:

• Real-time stock level checks during order processing
• Inventory reporting and analytics
• Product availability displays on the storefront
• Low stock alerts and notifications

Database Schema

Core Tables

inventory_projection

• product_id (UUID) - Primary key, references the product
• sku (VARCHAR) - Stock keeping unit identifier
• available_quantity (INTEGER) - Current available stock
• reserved_quantity (INTEGER) - Stock reserved for pending orders
• total_quantity (INTEGER) - Total physical stock
• reorder_point (INTEGER) - Minimum stock threshold
• last_updated (TIMESTAMP) - When this record was last updated
• version (BIGINT) - Event sourcing version number

product_locations

• product_id (UUID) - Foreign key to inventory_projection
• warehouse_id (UUID) - Warehouse identifier
• location_code (VARCHAR) - Specific location within warehouse
• quantity (INTEGER) - Quantity at this location
• last_counted (TIMESTAMP) - Last physical count date

stock_movements_summary

• product_id (UUID) - Product identifier
• movement_date (DATE) - Date of movement
• inbound_quantity (INTEGER) - Total items received
• outbound_quantity (INTEGER) - Total items shipped
• adjustment_quantity (INTEGER) - Manual adjustments
• ending_balance (INTEGER) - End of day balance

Data Sources

This read model is populated from the following event streams:

• InventoryReceived - Updates available quantity when new stock arrives
• InventoryReserved - Increases reserved quantity for orders
• InventoryReleased - Decreases reserved quantity when reservations expire
• InventoryAdjusted - Manual stock adjustments from warehouse operations
• InventoryTransferred - Stock movements between locations

Performance Characteristics

• Read Latency: < 5ms for single product queries
• Throughput: 50,000+ queries per second
• Data Freshness: Near real-time (< 100ms from event occurrence)
• Availability: 99.95% uptime SLA

Usage Patterns

High-Frequency Operations

• Stock availability checks during checkout
• Real-time inventory displays on product pages
• Order validation and reservation

Reporting Operations

• Daily inventory reports
• Low stock alerts
• Inventory turnover analysis
• Warehouse utilization metrics

Maintenance

Data Retention

• Transaction-level data: 2 years
• Summary data: 7 years
• Archived data moved to cold storage after retention period

Backup Strategy

• Full backups: Daily at 2 AM EST
• Incremental backups: Every 4 hours
• Point-in-time recovery available for 30 days
• Cross-region replication for disaster recovery

Monitoring

• Stock level discrepancy alerts
• Query performance monitoring
• Event processing lag alerts
• Database health checks every 5 minutes

Security

• Access Control: Role-based access with principle of least privilege
• Encryption: Data encrypted at rest using AES-256
• Network Security: VPC isolation with private subnets
• Audit Logging: All data access logged for compliance

Dependencies

• Event Store: Primary source of inventory events
• Message Bus: RabbitMQ for event consumption
• Cache Layer: Redis for frequently accessed data
• Monitoring: Prometheus and Grafana for metrics

Contact Information

For questions about this read model, please contact:

• Primary: Inventory Team (inventory@acmecorp.com)
• On-call: Use PagerDuty escalation policy “Inventory-ReadModel”
• Architecture Questions: Sarah Mitchell (s.mitchell@acmecorp.com)