Modern applications demand updated modeling patterns:
Relational and NoSQL Models
- Entity-Relationship (ER) Pattern: Traditional relational model using entities and relationships.
- Document Model: Stores unstructured data (JSON/XML); used in MongoDB.
- Columnar Model: Column-wise storage for high-performance analytics (Snowflake, BigQuery).
- Graph Model: Optimized for complex relationships, e.g., fraud detection, social networks.
Emerging Trends
- Big Data & Real-Time Data (RTD): Focus on traceability, data quality, auditing, and versioning.
- Microservices Architecture: Use database-per-service pattern for decoupled, scalable services.
- Caching Patterns: Key-value stores (Redis) for fast data access.
- Scalability & Parallelism: Columnar databases allow horizontal scaling and parallel reads.
Data Ingestion & Metadata
- Ingestion Layer: Flexible schemas to store unstructured data from multiple sources.
- Metadata Schemas: Define rules for cleansing and validation; ensure consistent, high-quality datasets.