Relational storage engine

The problem

Large relational datasets and concurrent read/write pressure can create query bottlenecks and deadlocks.

The solution

Normalized schemas, partition schemes, disk indexing, health checks, and connection pooling.

System architecture

Concurrent benchmark clients → connection pool → PostgreSQL transaction and storage layer.

Engineering challenges

Maintaining ACID consistency while resolving deadlocks and isolating resource bottlenecks.

Results & impact

• Modeled more than 500,000 records
• Reduced analytical query latency from 2.5 seconds to under 1 second
• Profiled execution plans and buffer pools to eliminate full-table scans

Results reported in the supplied resume; independent benchmarks are not provided.