Database Architecture That Scales Without Breaking

Every slow page load, every duplicate record, every report that takes minutes to generate traces back to database decisions made on day one. We get those decisions right from the start.

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more costly to fix data architecture problems in production compared to catching them during the design phase

IBM Systems Sciences Institute

Database Design

Properly structured database architecture that stores your data efficiently, enforces integrity constraints, and supports fast queries as your dataset grows from thousands to millions of records.

What's Included

Everything you get with our Database Design

Entity-Relationship Diagram

Complete visual schema showing all tables, relationships, indexes, and constraints, serving as the canonical reference for your data architecture

Query Performance Analysis

Benchmarked query execution plans for your most critical data operations, with indexing strategies to keep response times under 100ms

Migration and Seed Scripts

Version-controlled database migration files and seed data scripts so your schema is reproducible, testable, and deployable across environments

Our Database Design Process

Data Requirements Analysis

We work with your team to identify every entity, relationship, and access pattern your application needs. This produces a comprehensive data dictionary that becomes the foundation for schema design.

Schema Design and Normalization

We create an entity-relationship diagram with proper normalization, define data types and constraints, and design the indexing strategy based on your application's read/write patterns.

Performance Testing and Optimization

We load-test the schema with realistic data volumes, analyze query execution plans, and tune indexes and query patterns until critical operations meet performance benchmarks.

Migration Scripts and Documentation

We deliver version-controlled migration files, seed data scripts, and complete documentation of the schema design decisions, so your team understands not just what was built but why.

Key Benefits

Queries that stay fast as data grows

Strategic indexing, query optimization, and proper normalization ensure your application's response times remain consistent as your dataset scales from thousands to millions of records, avoiding the slow-query cliff that surprises growing businesses.

Data integrity you can trust

Foreign key constraints, check constraints, unique indexes, and transaction boundaries ensure your data remains consistent and valid. No duplicate records, no orphaned references, no silent data corruption that undermines your reports and decisions.

Schema changes without downtime

Version-controlled migrations and backward-compatible schema evolution strategies let your team modify the database structure as requirements change, without taking the application offline or risking data loss.

Research & Evidence

Backed by industry research and proven results

Relative Cost of Fixing Defects

The cost to fix a defect found during production is 6x that of one identified during design, and database schema changes in production are among the most disruptive

IBM Systems Sciences Institute (2008)

Performance Impact of Load Time

A 100ms delay in page load time, often caused by slow database queries, can reduce conversion rates by 7%

Akamai (2017)

Frequently Asked Questions

Should we use a relational database or NoSQL?

It depends on your data relationships and access patterns. Relational databases like PostgreSQL excel when your data has clear relationships, you need transactional integrity, and you run complex queries. NoSQL databases like MongoDB work well for document-oriented data, flexible schemas, and high-volume writes. Many applications benefit from both. We will recommend the right choice based on your specific data characteristics.

Our database queries are already slow. Can you help?

Yes. We start with a query performance audit, analyzing execution plans for your slowest queries and identifying missing indexes, suboptimal joins, and N+1 query patterns. Most slow databases can see order-of-magnitude improvements through indexing changes and query rewrites without any schema migration.

How do you handle database migrations in production?

We use version-controlled migration tools that apply schema changes incrementally and reversibly. For zero-downtime deployments, we use expand-and-contract patterns: adding new columns or tables first, migrating data, updating application code, then removing old structures. This approach ensures your application stays online throughout the migration.

What about data backups and disaster recovery?

Every database we deploy includes automated daily backups, point-in-time recovery capability, and a documented restore procedure that your team has tested before launch. We configure backup retention policies, cross-region replication for critical systems, and monitoring alerts for backup failures.

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Build on a Data Foundation That Lasts

Whether you are designing a new database or fixing a slow one, we will architect a schema that performs reliably at any scale.

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