Database Work That Makes Applications Fast
Slow applications are usually slow databases. We find the queries and the model decisions causing it, fix them safely on live data, and leave the schema documented and properly indexed.
Overview
What is Database Design and Optimization?
Database design is the work of structuring tables, relationships, and constraints so data stays consistent and queries stay fast. Database optimization is the work of measuring real query performance and improving it through indexing, query rewriting, schema changes, or configuration.
Performance work starts with measurement rather than opinion: the slowest queries by total time, the ones running most often, and the execution plans behind them. Fixes are then ordered by effect, from missing indexes and rewritten queries through to changes in the model itself. New systems get the same attention earlier, while a schema still costs nothing to change: constraints that protect the data, indexes for the access patterns you actually have, and migrations that can run on a live database without a maintenance window.
Capabilities and features
A Model That Protects the Data
Tables, relationships, and constraints designed so invalid data cannot be written in the first place, rather than being cleaned up in reports later. Access patterns are considered at design time, because indexes follow queries and not the other way around.
- Normalised design with the right constraints and defaults
- Indexes planned against real access patterns
- A documented model your developers can read

Measure, Then Fix What Actually Hurts
Slow query logs and execution plans identify the queries costing the most total time, which is rarely the one people complain about. Fixes go in order of effect, and each change is verified under realistic volume rather than on a small development dataset.
- Slow query and execution plan analysis with a ranked list
- Indexing, query rewriting, and caching where it earns its place
- Before and after numbers on realistic data volume

Changes That Run Without a Maintenance Window
Schema changes and data migrations designed to run online, in reversible steps, with a tested rollback. Where volume is the real problem, partitioning, read replicas, or archiving are used instead of buying a bigger server indefinitely.
- Online, reversible migrations tested against a copy of live data
- Partitioning, replicas, and archiving where volume demands it
- Backup and restore actually tested, not assumed

The real impact
Why it matters
A slow page is often one missing index, and a wrong report is often one missing constraint. Both are cheap to fix early and expensive once the data has grown and half the application depends on the shape it is in.
The global database management market is growing at over 12% annually. Database infrastructure is the foundation for every application, analytics system, and AI model your business runs.
Source: Gartner / Market Research
In most applications, the database is the bottleneck. Slow queries, missing indexes, and poor schema design cause the majority of performance problems that users experience as slow page loads.
Source: Industry consensus / Percona
Bad database design leads to data inconsistency, duplication, and integrity issues. These errors compound through every report, dashboard, and business decision downstream.
Source: Precisely / Data Integrity Trends Report, 2025
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FAQ
Frequently asked questions
Everything you need to know about this service.
PostgreSQL is the sensible default for most applications and does more than people expect, including JSON and search. MySQL fits existing ecosystems well. MongoDB suits genuinely document shaped data. The decision follows your access patterns and your team, and it gets written down with the reasons.
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