PostgreSQL: - Use partial indexes for filtered queries: Use partial indexes for filtered queries: - Implement BRIN indexes for large, naturally ordered tables (like timestamps) Implement BRIN indexes for large, naturally ordered tables (like timestamps) - Consider GIN indexes for JSONB or full-text search Consider GIN indexes for JSONB or full-text search - Regularly monitor unused indexes with Regularly monitor unused indexes with Oracle: - Implement bitmap indexes for low-cardinality columns in data warehouses Implement bitmap indexes for low-cardinality columns in data warehouses - Use function-based indexes: Use function-based indexes: - Consider reverse key indexes for sequential keys to reduce contention Consider reverse key indexes for sequential keys to reduce contention - Monitor index usage with Monitor index usage with Common Strategy: Index only what you need. Over-indexing slows down writes. Use the EXPLAIN/EXPLAIN PLAN to verify index usage.

PostgreSQL: - Use to understand query execution plans Use to understand query execution plans - Enable extension for query monitoring Enable extension for query monitoring - Look for sequential scans on large tables (often indicates missing indexes) Look for sequential scans on large tables (often indicates missing indexes) - Parameterize queries to enable plan reuse Parameterize queries to enable plan reuse Oracle: - Utilize SQL Tuning Advisor and SQL Access Advisor Utilize SQL Tuning Advisor and SQL Access Advisor - Monitor and for expensive queries Monitor and for expensive queries - Implement bind variables to reduce hard parsing Implement bind variables to reduce hard parsing - Consider SQL Plan Management for plan stability Consider SQL Plan Management for plan stability Pro Tip: Regularly identify and optimize your top 5-10 most expensive queries—they typically account for 80% of your load.

PostgreSQL: - Configure appropriately (typically 100-500) Configure appropriately (typically 100-500) - Use connection pooling with PgBouncer or application-level pools Use connection pooling with PgBouncer or application-level pools - Set to prevent idle connections Set to prevent idle connections - Monitor connections with Monitor connections with Oracle: - Implement Database Resident Connection Pooling (DRCP) for web applications Implement Database Resident Connection Pooling (DRCP) for web applications - Configure appropriate and parameters Configure appropriate and parameters - Use Oracle Connection Manager for multiplexing Use Oracle Connection Manager for multiplexing - Monitor with and Monitor with and Critical Insight: Each connection consumes memory. More connections ≠ better performance. Pool connections whenever possible.

PostgreSQL: - Set to 25-40% of available RAM (not exceeding 8GB without specific testing) Set to 25-40% of available RAM (not exceeding 8GB without specific testing) - Configure to estimate available disk cache Configure to estimate available disk cache - Adjust for sorting/hashing operations (default is often too low) Adjust for sorting/hashing operations (default is often too low) - Set higher for maintenance tasks Set higher for maintenance tasks Oracle: - Configure SGA (System Global Area) appropriately for buffer cache, shared pool Configure SGA (System Global Area) appropriately for buffer cache, shared pool - Set PGA (Program Global Area) for sorting and hash joins Set PGA (Program Global Area) for sorting and hash joins - Use Automatic Memory Management (AMM) or Automatic Shared Memory Management (ASMM) Use Automatic Memory Management (AMM) or Automatic Shared Memory Management (ASMM) - Monitor memory usage with and Monitor memory usage with and Memory Rule: Database performance is often about minimizing disk I/O through effective memory utilization.

PostgreSQL: - Separate tables, indexes, and WAL logs onto different physical disks Separate tables, indexes, and WAL logs onto different physical disks - Consider tablespaces for physical data separation Consider tablespaces for physical data separation - Use appropriate for update-heavy tables (90-95 instead of 100) Use appropriate for update-heavy tables (90-95 instead of 100) - Implement partitioning for large tables Implement partitioning for large tables Oracle: - Implement Automatic Storage Management (ASM) for simplified storage management Implement Automatic Storage Management (ASM) for simplified storage management - Separate redo logs, data files, and temporary tablespaces Separate redo logs, data files, and temporary tablespaces - Use locally managed tablespaces with automatic segment-space management Use locally managed tablespaces with automatic segment-space management - Implement partitioning for tables exceeding 2GB Implement partitioning for tables exceeding 2GB Storage Principle: Balance I/O across physical devices. Sequential I/O is significantly faster than random I/O.

PostgreSQL (Critical): - Configure appropriately based on update frequency Configure appropriately based on update frequency - Set and Set and - Monitor bloat with extension Monitor bloat with extension - Schedule regular and during maintenance windows Schedule regular and during maintenance windows Oracle: - Implement Automatic Segment Advisor for space reclamation Implement Automatic Segment Advisor for space reclamation - Schedule regular statistics gathering with Schedule regular statistics gathering with - Use online segment shrink for heap tables Use online segment shrink for heap tables - Consider table compression for historical data Consider table compression for historical data Maintenance Insight: Regular maintenance prevents performance degradation over time, especially for OLTP workloads.

PostgreSQL: - Size WAL files appropriately ( in PG 11+) Size WAL files appropriately ( in PG 11+) - Configure (typically 16MB) Configure (typically 16MB) - Consider trade-offs (performance vs. durability) Consider trade-offs (performance vs. durability) - Implement WAL archiving and replication strategically Implement WAL archiving and replication strategically Oracle: - Size redo logs appropriately (switch every 15-30 minutes) Size redo logs appropriately (switch every 15-30 minutes) - Place redo logs on fast, dedicated storage Place redo logs on fast, dedicated storage - Consider operations for bulk loads when recoverability isn’t critical Consider operations for bulk loads when recoverability isn’t critical - Configure appropriately (typically several MB) Configure appropriately (typically several MB) Logging Principle: Log configuration balances performance with durability requirements based on your RPO/RTO.

PostgreSQL: - Use prepared statements for repeated queries Use prepared statements for repeated queries - Implement materialized views for expensive aggregations Implement materialized views for expensive aggregations - Consider extension for critical tables Consider extension for critical tables - Use connection-level caches judiciously Use connection-level caches judiciously Oracle: - Implement Result Cache for deterministic functions Implement Result Cache for deterministic functions - Use Client-Side Query Cache in OCI applications Use Client-Side Query Cache in OCI applications - Consider In-Memory Column Store (extra cost) for analytic workloads Consider In-Memory Column Store (extra cost) for analytic workloads - Implement Flashback Query for point-in-time reporting Implement Flashback Query for point-in-time reporting Caching Wisdom: Cache at the right level—application, database, or OS—to avoid unnecessary database hits.

PostgreSQL (10+): - Configure Configure - Set and Set and - Use to include leader in parallel scans Use to include leader in parallel scans - Consider for parallel query eligibility Consider for parallel query eligibility Oracle: - Configure appropriately Configure appropriately - Use hints or clause for appropriate operations Use hints or clause for appropriate operations - Consider Automatic Degree of Parallelism (Auto DOP) Consider Automatic Degree of Parallelism (Auto DOP) - Monitor parallel execution with Monitor parallel execution with Parallelization Note: Parallel queries consume significant resources. Use for appropriate workloads (large scans, aggregations) only.

PostgreSQL: - Enable and monitor Enable and monitor - Use and Use and - Implement for real-time monitoring Implement for real-time monitoring - Consider tools like pgBadger for log analysis Consider tools like pgBadger for log analysis Oracle: - Utilize Automatic Workload Repository (AWR) reports Utilize Automatic Workload Repository (AWR) reports - Implement Active Session History (ASH) for real-time diagnostics Implement Active Session History (ASH) for real-time diagnostics - Use Enterprise Manager or Cloud Control Use Enterprise Manager or Cloud Control - Monitor wait events with Monitor wait events with Monitoring Philosophy: You can’t optimize what you don’t measure. Establish baselines and monitor trends, not just thresholds.