Start from evidence
We capture a baseline of query latency, throughput, waits and resource use under real load. Tuning priorities come from the workload, not from generic checklists.
Database Performance Tuning & Query Optimization
Find out exactly why a database is slow, fix the queries, indexes and settings that matter most, and prove the improvement with before-and-after measurements.
From a slow page to the exact query behind it
We trace slow user journeys down to the statements, plans and waits that cause them, then fix what moves the numbers most.
- Execution-plan and wait-event analysis
- Index design and clean-up
- Configuration and memory tuning
- Lock, deadlock and contention fixes
Who it's for
Teams usually come to us in one of these situations.
Slow applications
Pages and APIs that slow down as data grows or traffic peaks.
High cloud database bills
Oversized instances bought to hide inefficient queries.
Teams before a launch
Products that need confidence they will cope with new load.
Our tuning method
Baseline
Measure latency, throughput, waits and resource use under real load.
Diagnose
Rank the top statements by total cost and find their root causes.
Optimize
Indexes, query rewrites, statistics, configuration and partitioning.
Verify
Compare against the baseline and add regression guards.
What makes our tuning stick
Fix the biggest wins first
Most gains come from a small number of queries: missing or unused indexes, inefficient joins, N+1 patterns and plans that changed after a data or version change.
Keep it fast
Regression checks, plan monitoring and capacity forecasts help the improvements survive the next release and the next year of data growth.
Engine-specific expertise
We tune each engine on its own terms: wait statistics and Query Store on SQL Server, EXPLAIN ANALYZE, vacuum and bloat on PostgreSQL, InnoDB and the slow log on MySQL, the profiler and indexes on MongoDB, and merges and partitioning on ClickHouse.
Load testing and capacity planning
Where useful, we replay or simulate realistic load to confirm improvements and find the next bottleneck, then forecast when you will need more capacity.
Common situations we solve
Real problems we are asked to fix, what we do about them and the result to expect.
The situation
Pages that load in a second take ten at month end
We capture the workload during peaks, find the queries and locks that degrade under load, and fix indexes, plans and batch schedules.
Consistent speed when it matters most
The situation
The database server keeps getting bigger and still struggles
We measure where CPU, memory and I/O really go, remove inefficient queries, and right-size the instance only after the waste is gone.
Better performance on smaller hardware
The situation
Reports lock tables that customers need
We rework reporting queries, add read replicas or snapshots, and separate analytical load from transactions.
Reports and customers no longer compete
The situation
A launch or campaign is coming and nobody knows the limits
We load test realistic traffic, tune the bottlenecks we find and give you a capacity plan with clear headroom numbers.
Launch with known limits, not hope
What you get
Faster queries
The statements that matter most, measurably faster against a baseline.
Lower resource use
Less CPU, I/O and memory per request, often allowing smaller instances.
Lasting gains
Regression checks so improvements survive future releases.
What you receive
- Workload baseline and top-query report
- Prioritised tuning backlog with expected impact
- Tested index and query changes
- Configuration recommendations per engine
- Before-and-after performance comparison
- Capacity forecast for the next 12 months
Frequently asked questions
Will tuning require application changes?
Often the biggest wins come from indexes and configuration alone. Where query rewrites help, we prepare and test them with your developers.
Is tuning safe on production?
Changes are tested on a copy or staging environment first and applied through your change process with rollback steps.
Can you tune managed cloud databases?
Yes. Amazon RDS, Aurora, Azure SQL and Cloud SQL expose parameters, performance insights and query statistics that we use the same way.
How long does a tuning engagement take?
A focused engagement typically runs two to four weeks, from baseline to verified improvements, depending on the size of the workload.
Can you tune third-party applications?
Often yes. Indexes, statistics and configuration can help even when the application's queries cannot be changed.
Do you guarantee a specific speed-up?
No fixed figure is promised before measuring. We share expected impact per change and report the measured result.
Talk to us about Performance Tuning & Optimization.
Request a scoped cloud assessment, or start with a free DevOps and SRE consultation. Talk to us about services, AI solutions or enterprise development.