1. Identifying Slow and Inefficient Queries

• We use advanced profiling tools such as EXPLAIN ANALYZE, pg_stat_statements , and auto_explain to detect slow queries.
• We examine PostgreSQL logs and execution metrics to identify underlying performance issues that may not be immediately visible.
• We assess ORM-generated queries in Odoo that can result in unnecessary joins, subqueries, or redundant calls.

2. Improving SQL Query Performance

• Our experts rewrite inefficient SQL and ORM queries to be more execution-friendly.
• We apply indexing strategies (B-tree, GIN, partial, and multicolumn indexes) to accelerate data access.
• When appropriate, we implement query partitioning, reducing the dataset size for faster reads and writes.
• We break down complex and heavy queries into smaller, more efficient components to minimize CPU load and disk access.

3. Optimizing Odoo ORM Interactions

• We analyze and optimize custom module code and business logic to make better use of Odoo’s ORM, improving overall system efficiency.
• Redundant and repetitive queries from poorly designed loops or misused ORM methods are eliminated.
• We introduce lazy loading and batch fetching where applicable to avoid unnecessary database calls.

4. Monitoring and Continuous Analysis

• We deploy monitoring tools like pg_stat_monitor, pgBadger, and Prometheus/Grafana to provide real-time visibility into query performance.
• We set up alerts and dashboards to monitor spikes in query time, lock contention, and deadlocks.