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Performance & Scalability
Query Optimization Services
Database query optimization services. We analyze and fix slow queries, design efficient indexes, and restructure data access patterns for orders-of-magnitude improvements.
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Avg Performance Gains
99.9%
Availability
1M+
RPM Capacity
<50ms
P95 Latency
Service Category
Query Performance Engineering
Ideal For
Applications with slow database queries causing latency, high CPU usage, or lock contention issues.
Timeline
1 – 3 weeks
Why Choose MicrocosmWorks for Query Optimization?
Slow queries are the #1 cause of application performance problems. We use systematic analysis — EXPLAIN plans, statistics, access patterns, and workload profiling — to identify exactly why queries are slow and implement solutions that deliver 10-100x speed improvements. No guessing, just data-driven optimization.
Our Query Optimization Capabilities
- Query Analysis & EXPLAIN — Deep dive into execution plans, identify sequential scans, join order problems, and suboptimal planner choices.
- Index Strategy — Design comprehensive indexing strategies including composite indexes, partial indexes, covering indexes, and GIN/GiST indexes for special data types.
- Query Rewriting — Restructure queries to eliminate N+1 patterns, optimize CTEs, replace correlated subqueries, and leverage window functions.
- Schema Optimization — Normalize or denormalize strategically, add materialized views, and restructure tables for your actual access patterns.
- Connection & Pool Optimization — Tune connection pools, optimize transaction management, and reduce lock contention for concurrent workloads.
- Monitoring & Alerting — Set up slow query logging, pg_stat_statements tracking, and automated alerts for query performance regression.
Technology Stack
We work primarily with PostgreSQL (including Aurora, Neon, Supabase), MySQL, and MongoDB. Our analysis uses pg_stat_statements, auto_explain, pganalyze, and custom query profiling. Solutions include indexing strategies, query rewrites, materialized views, and application-level changes.
Who This Is For
Applications with slow database queries causing user-facing latency, high database CPU usage, or lock contention. Whether it's a few critical queries dragging down your dashboard or systemic query patterns causing widespread slowness, we fix it.
Our Process
1
Query Audit
Identify top slow queries using pg_stat_statements, analyze access patterns, and measure baseline performance.
2
Root Cause Analysis
Run EXPLAIN ANALYZE on each slow query, identify missing indexes, bad joins, and suboptimal patterns.
3
Optimization
Implement index changes, query rewrites, schema adjustments, and caching for most impactful queries.
4
Validation
Benchmark optimized queries, verify no regressions in other queries, and load test under concurrent access.
5
Ongoing Monitoring
Set up slow query tracking, regression alerts, and periodic review cadence for continued optimization.
Technology Stack
Databases
PostgreSQLMySQLMongoDBAuroraNeon
Analysis
pg_stat_statementsEXPLAIN ANALYZEauto_explainpganalyze
Optimization
IndexesMaterialized ViewsQuery RewritingPartitioning
Monitoring
pganalyzeDataDogPrometheusCustom Dashboards
Industries We Serve
SaaSE-CommerceFinTechAnalyticsHealthcareEnterprise
Ready to Fix Your Slow Queries?
Let's turn your database from a bottleneck into a performance asset with targeted query optimization.
Frequently Asked Questions
We analyze execution plans with EXPLAIN ANALYZE, identify missing or redundant indexes, rewrite subqueries as joins, eliminate N+1 patterns, and optimize table statistics to ensure the query planner makes optimal decisions.
Query optimization services at MicrocosmWorks range from $20-$45/hour. We typically start by profiling your slowest queries and fixing the highest-impact ones first, delivering measurable improvements within days.
Yes, we optimize large-scale databases using table partitioning, partial indexes, materialized views, covering indexes, and query restructuring to maintain sub-second response times even on tables with billions of rows.
Absolutely. We audit ORM-generated SQL from Django, SQLAlchemy, Prisma, Hibernate, and other ORMs, identifying eager/lazy loading issues, unnecessary joins, and N+1 patterns, then optimize either the ORM usage or add raw SQL where needed.
We set up automated query performance monitoring using pg_stat_statements or similar tools, create regression test suites for critical queries, and configure alerts that trigger when query execution times exceed established baselines.