Database Design & Architecture
The foundation of every fast application is a well-designed database. We build data architectures that perform at scale.
Your database schema is the most consequential architectural decision in your application. Get it right, and queries are fast, data integrity is guaranteed, and new features slot in cleanly. Get it wrong, and you spend years working around a foundation that fights you at every turn.
We specialize in database design for growing applications. We have helped companies redesign schemas that cut query times from seconds to milliseconds, migrate from one database engine to another without downtime, and build data architectures that handle millions of records without breaking a sweat.
Whether you are starting a new project and want to get the schema right from day one, or you have an existing application with performance problems that need expert optimization, we can help.
What You Get
Schema Design
Normalized relational schemas, document model design, and hybrid approaches — choosing the right structure for your data access patterns and consistency requirements.
Query Optimization
EXPLAIN ANALYZE-driven optimization, index strategy, query rewriting, and connection pooling to eliminate slow queries and reduce database load.
Migration Services
Zero-downtime database migrations, engine migrations (MySQL to PostgreSQL, MongoDB to PostgreSQL), and schema evolution strategies.
Performance Auditing
Comprehensive database audits identifying missing indexes, N+1 queries, lock contention, bloated tables, and configuration issues.
Multi-Database Architecture
PostgreSQL for transactional data, Redis for caching and sessions, Elasticsearch for search — each tool used where it excels.
Backup & Recovery
Automated backup strategies, point-in-time recovery testing, replication setup, and disaster recovery planning.
PostgreSQL: Our Database of Choice
For most applications, PostgreSQL is our default recommendation. It handles relational data exceptionally well, but it also supports JSON columns, full-text search, geospatial queries (PostGIS), and time-series data — reducing the need for specialized databases in many cases.
We leverage PostgreSQL features that many teams overlook: partial indexes for sparse data, materialized views for expensive aggregations, row-level security for multi-tenant applications, and LISTEN/NOTIFY for lightweight real-time updates. These built-in features often eliminate the need for additional infrastructure.
For connection management, we configure PgBouncer or the built-in connection pooling in frameworks like Prisma, ensuring your application handles connection limits gracefully under load.
Schema Design Principles
We design schemas based on your actual query patterns, not just the entity relationships. A schema that looks perfect in an ER diagram can perform terribly if the most common queries require joining six tables. We balance normalization with practical denormalization, using materialized views and computed columns where they eliminate expensive runtime joins.
For multi-tenant applications, we evaluate the trade-offs between shared schema (tenant_id columns), schema-per-tenant, and database-per-tenant approaches based on your data isolation requirements, query complexity, and expected tenant count.
Every schema we design includes proper constraints: foreign keys, NOT NULL where appropriate, CHECK constraints for business rules, and unique indexes for natural keys. These constraints are not optional — they are the database enforcing your business rules, catching bugs that application code might miss.
Performance Optimization and Monitoring
Database optimization starts with measurement, not guessing. We enable pg_stat_statements to identify your slowest and most frequent queries, analyze execution plans with EXPLAIN (ANALYZE, BUFFERS), and correlate database metrics with application performance data.
Common wins we find during audits include: missing indexes on foreign key columns (causing slow joins), sequential scans on large tables that should use index scans, N+1 query patterns in the application layer, and over-broad SELECT * queries that fetch columns never used by the application. After optimization, we set up monitoring with tools like pganalyze or custom Grafana dashboards that track query performance over time, alerting when query times degrade so problems are caught before users notice.
Technologies We Use
Frequently Asked Questions
How do you handle zero-downtime database migrations?
Should I use PostgreSQL or MongoDB?
My database queries are slow. Can you help?
How much does database optimization cost?
Database Holding You Back?
Let us audit your database and show you exactly where the bottlenecks are — and how to fix them.