database-architecture

Database architecture selection requires evaluating workload characteristics like data shape, growth rate, latency targets, and consistency needs to identify the optimal platform. This approach matches OLTP, OLAP, relational, and non-relational systems to specific enterprise requirements.

Canonical data stores serve as the primary source of truth, while derived stores, cache layers, and search indexes are built from the canonical store to optimize read latency and specific query patterns. This separation balances consistency with performance.

Database partitioning and replication design uses explicit decision principles based on your workload profile to distribute data and ensure availability. Architecture-level guidance scales systems while maintaining governance and consistency requirements.

The database architecture approach supports both OLTP and OLAP workloads across enterprise-grade systems. It classifies workload needs and proposes appropriate relational, non-relational, document, key-value, and graph store platforms.

Add a cache layer or search index to your database architecture when read latency targets exceed canonical store capabilities or when complex search queries degrade performance. The design defines these layers based on specific workload profile demands.