PostgreSQL Database Design & Optimisation
TICS designs and optimises PostgreSQL databases for scalability, reliability, and performance, covering schema architecture, query tuning, migration strategies, and operational best practices.
Overview
TICS provides specialist PostgreSQL database services that address the full lifecycle of a relational data layer: initial schema design, ORM integration, query performance optimisation, data migration from legacy systems, high-availability configuration, and ongoing operational governance. PostgreSQL's combination of ACID compliance, rich data types, powerful indexing capabilities, and active open-source community makes it the preferred database platform for TICS-built applications and for many client data modernisation projects.
For greenfield applications, TICS designs normalised schemas informed by domain-driven design principles, selecting appropriate data types, establishing referential integrity constraints, planning index strategies for anticipated query patterns, and setting up partitioning schemes for tables with high data volumes. ORM layer configuration using Prisma or TypeORM is treated as an engineering concern in its own right, with careful attention to N+1 query prevention, eager loading strategies, and transaction boundaries.
For existing PostgreSQL environments experiencing performance degradation or scaling challenges, TICS conducts systematic query performance analysis using EXPLAIN ANALYSE, pg_stat_statements, and custom profiling queries to identify the highest-impact optimisation opportunities. Remediation typically spans index additions, query rewrites, connection pooling configuration via PgBouncer, vacuuming and bloat management, and in high-traffic scenarios, read replica configuration and caching layer introduction with Redis.
Key Capabilities
Schema design with normalisation, data type selection, constraint definition, and partitioning strategy
Query performance analysis using EXPLAIN ANALYSE and pg_stat_statements with targeted optimisation
Prisma and TypeORM configuration including relationship mapping, migration management, and query optimisation
High-availability architecture design with primary-replica replication and automated failover
Data migration planning and execution from legacy databases including MySQL, MSSQL, and Oracle
Technology Stack
Use Cases
Real-world scenarios where this service delivers impact
Database Performance Rescue for a SaaS Platform
A B2B SaaS company with 500 active tenants experienced severe query degradation as their PostgreSQL database grew beyond 200 GB, with report generation times exceeding 45 seconds. TICS conducted a two-week performance audit that identified 12 missing indexes, 8 N+1 query patterns generated by ORM misuse, and 3 unbounded table scans in core report queries. After implementing the remediation plan, average report generation time dropped to under 2 seconds and database CPU utilisation fell by 60%.
Multi-Tenant Schema Design for a Property Management Platform
A property technology startup building a multi-tenant SaaS platform needed a database architecture that would isolate tenant data, scale to 10,000 properties per tenant, and support complex analytical queries across lease, payment, and maintenance data. TICS designed a row-level security-based multi-tenancy schema with Prisma ORM integration, table partitioning on date ranges for historical data, and a separate read replica configuration for analytical queries, providing a foundation that scaled from 10 to 800 tenants without architectural changes.
Oracle to PostgreSQL Migration for a Healthcare Information System
A healthcare technology company sought to exit an expensive Oracle Database licence by migrating their patient information system to PostgreSQL. TICS led the migration covering schema translation, stored procedure rewriting, data migration with reconciliation, application query layer adaptation, and performance validation. The migration was completed with zero data loss, a 94% reduction in database licensing cost, and no degradation in application query performance.
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