Building Autonomous PostgreSQL
Always optimized for performance and stability
DBtune’s Agentic AI for autonomous PostgreSQL optimization brings together server parameter tuning, index optimization and autovacuum monitoring to help keep PostgreSQL operational, stable and tuned for high performance, while reducing manual database optimization work.
DBtune helps teams deliver an exceptional end-user experience, free up capacity for strategic priorities and innovation, and get more value from existing infrastructure.
A unified approach to PostgreSQL optimization
Server parameter tuning
DBtune tests PostgreSQL server parameter configurations against the workload and machine type and applies the best-performing settings automatically, or lets the user approve changes first.
Index optimization
DBtune identifies and ranks index opportunities based on the workload, showing the expected impact, cost and DDL. This includes recommendations for new indexes that can significantly speed up specific critical queries, as well as existing indexes that may require maintenance due to bloat or removal because they are obsolete or duplicates. DBtune brings advanced index analysis and prioritization capabilities to the team, while keeping every change under their control. The user remains in the loop and decides whether to apply each recommendation.
Autovacuum monitoring
DBtune identifies where autovacuum is falling behind and helps diagnose what is causing the problem.
Product resources
DBtune product paper
A deeper look at DBtune’s approach to autonomous PostgreSQL optimization.
Download the product paperSee DBtune in action
A demo to see DBtune’s approach to autonomous PostgreSQL optimization.
Watch the demo
Discover the value DBtune can deliver in your own environment
See what DBtune can deliver in your own PostgreSQL environment. A typical enterprise Proof of Value takes two weeks and provides measurable evidence of performance improvement, operational impact and reduced manual optimization work.