Database Optimization

Optimize any database technology without assuming MongoDB, PostgreSQL, MySQL, an ORM, or a particular hosting provider. Inspect evidence before making recommendations.

First: detect the data layer

Search the repository for database drivers, ORM/query-builder packages, connection configuration, schemas/models, migrations, indexes, constraints, repositories, raw queries, transactions, seeds, caches, search systems, background jobs, analytics workloads, tests, deployment configuration, and monitoring.

Identify:

• database engines, versions, extensions, topology, hosting, and environment;
• drivers, ORM/query layer, versions, pooling, retry, and timeout configuration;
• schemas, relationships, constraints, indexes, migrations, and ownership;
• high-traffic read/write paths, data volume/growth, concurrency, latency, and throughput;
• replicas, partitions/shards, caches, queues, backup/restore, retention, and observability.

If a data layer exists, explain its current design, healthy choices, measured or evidenced problems, and an ordered safe improvement plan. If none exists, design the smallest suitable persistence approach from the product's consistency, query, scale, security, and operational requirements.

Do not upgrade a database, driver, or ORM silently. Check release notes, compatibility, migration requirements, and rollback before changing versions.