What database technologies do you use?

Advisory Apps selects database technologies based on each project's specific data requirements. We work with relational, document-based, key-value, and real-time databases — often combining multiple systems within a single architecture for optimal performance.

Relational Databases

• MySQL: Our default relational database — reliable, widely supported, and proven across hundreds of our projects with Node.js and Laravel backends. Well-suited for web applications, SaaS platforms, and content management systems.
• PostgreSQL: For applications requiring advanced query capabilities, JSON data types, full-text search, or complex relational modelling. Used in our SaaS platforms where data integrity and analytical workloads are critical.

NoSQL & Document Databases

• MongoDB: For high-volume programs — large-scale data ingestion, IoT telemetry, event logging, and applications with flexible or rapidly evolving data schemas where document-based storage simplifies development.
• Firebase Firestore: Real-time database for mobile and web apps requiring instant data synchronisation across clients. Commonly used in chat features, live dashboards, and collaborative tools.

Caching & Performance

• Redis: In-memory data store for session management, caching frequently accessed queries, rate limiting, job queues, and pub/sub messaging. We use Redis in most production applications to reduce database load and improve response times.

Enterprise & Legacy Databases

We have hands-on experience integrating with enterprise database systems for clients who require it:

• Oracle Database: Our Perodua SA app integrates directly with Oracle ERP, synchronising vehicle inventory, commission tracking, and sales data for 3,000+ advisors nationwide.
• Microsoft SQL Server (MSSQL): For organisations running Microsoft ecosystem infrastructure — we connect to existing MSSQL instances and build middleware layers as needed.

How We Choose

Database selection is driven by technical requirements, not preference. Key factors include:

• Data relationships: Highly relational data (e.g., ERP, financial systems) favours MySQL or PostgreSQL. Flexible schemas and high-volume ingestion suit MongoDB.
• Scale profile: Read-heavy applications benefit from Redis caching layers. Write-heavy IoT projects may use MongoDB or time-series optimisations.
• Compliance: PDPA and data residency requirements influence hosting location and encryption at rest configurations, as implemented in our security practices.
• Existing infrastructure: If your organisation already runs Oracle or SQL Server, we integrate rather than replace.

Our team will recommend the right database architecture during the requirements gathering phase. Contact us to start the conversation.