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.