Database Architecture That Determines Your Application's Speed Ceiling

Every slow page load, every timeout error, every scaling wall traces back to database decisions made on day one. We design database architectures with schema normalization, strategic indexing, and query optimization that perform at scale, not just in development.

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conversion loss per 100ms of latency, and database query time is the single largest contributor to API response latency in most applications

Akamai, 2017

Database Architecture

Database design with PostgreSQL, MongoDB, or hybrid approaches including schema design, indexing strategy, query optimization, migration planning, and scaling architecture.

What's Included

Everything you get with our Database Architecture

Schema Design and Data Modeling

Normalized schema design with entity-relationship diagrams, table definitions, constraint specifications, and indexing strategy optimized for your query patterns

Query Optimization and Indexing

EXPLAIN analysis of critical queries, composite index design, query restructuring for N+1 elimination, and connection pooling configuration

Migration and Backup Strategy

Version-controlled schema migrations, automated backup schedules, tested restore procedures, and zero-downtime migration planning for production databases

Our Database Architecture Process

Data Modeling and Schema Design

We analyze your domain, design the entity-relationship model, normalize the schema, define constraints, and plan the indexing strategy based on projected query patterns.

Database Setup and Configuration

We provision the database, configure connection pooling, set up replication for read scaling, and implement automated backups with tested restore procedures.

Query Optimization

We analyze critical queries with EXPLAIN, add strategic indexes, restructure inefficient queries, and eliminate N+1 patterns. Every optimization is benchmarked before and after.

Migration Strategy and Documentation

We set up version-controlled migrations, document the schema, and create runbooks for common database operations. Your team can evolve the schema safely and independently.

Key Benefits

Queries that stay fast as data grows

Strategic indexing based on your query patterns ensures that database operations that take 5ms with 10,000 rows still take 5ms with 10 million rows. We design indexes for the queries your application actually runs, not generic best practices.

Schema that prevents data anomalies

Proper normalization, foreign key constraints, and check constraints prevent the data inconsistencies that cause application bugs. The database enforces data integrity at the engine level, not relying on application code to validate.

Zero-downtime migrations

Schema changes in production require careful migration planning. We write migrations that add before they remove, use background data transformations, and deploy in stages so your application stays online throughout the process.

Research & Evidence

Backed by industry research and proven results

Web Performance Impact

100ms of latency costs 7% in conversions, and unoptimized database queries are the most common cause of API latency that exceeds 100ms

Akamai (2017)

Systems Sciences Institute

Production bugs cost 6x more to fix, and schema design mistakes are among the most expensive to fix because they require data migrations that affect every row

IBM (2020)

Frequently Asked Questions

Should we use PostgreSQL or MongoDB?

PostgreSQL for structured data with relationships, transactions, and complex queries: ecommerce, SaaS, financial applications. MongoDB for document-oriented data with flexible schemas and nested structures: content management, IoT, event logging. Many applications benefit from both: PostgreSQL for transactional data and MongoDB or Redis for caching and session storage.

Can you optimize an existing slow database?

Yes. We audit query performance with pg_stat_statements or equivalent, identify the slowest queries, add missing indexes, restructure inefficient patterns, and configure connection pooling. Typical improvements range from 3x to 10x for databases with no prior optimization.

How do you handle database migrations in production?

Additive migrations first: add the new column or table, deploy code that writes to both old and new structures, migrate existing data in the background, switch reads to the new structure, then remove the old one. Zero downtime throughout.

How long does database architecture take?

Schema design for a new application takes 1 to 2 weeks. Database optimization for an existing application takes 2 to 4 weeks. A complete database redesign with migration takes 4 to 8 weeks.

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Design a Database That Scales With Your Application, Not Against It

Tell us about your data requirements. We will design the schema and indexing strategy that keeps your application fast as data grows.

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