ddia-systems

To choose between storage engines, evaluate whether your workload is write-heavy or read-heavy. LSM trees optimize high write throughput, while B-trees provide faster read performance and predictable latency for read-intensive applications.

Partitioning data requires selecting a strategy like range or hash partitioning to distribute load evenly. Your partitioning strategy must align with your query patterns to prevent hotspots and ensure scalable throughput across nodes.

Multi-region replication introduces latency trade-offs between strong and eventual consistency. Strong consistency guarantees correct application semantics but increases write latency, while eventual consistency lowers latency but risks stale reads across regions.

Use document data models for workloads requiring flexible schemas and localized data aggregation. Relational models are better when your application needs strict transactional guarantees and multi-object integrity across normalized tables.

Evaluating transactional guarantees involves mapping your latency targets and durability needs against isolation levels. You must determine if your application semantics require strict serializability or can tolerate relaxed isolation for higher throughput.