Data architecture you can rely on
Koda Technology specialises in the design and development of database systems for businesses across New Zealand and Australia, the foundation that every portal, integration and platform we build sits on top of.
We work across relational systems including SQL Server, PostgreSQL and MariaDB, and NoSQL systems including MongoDB and Couchbase, replacing legacy database environments with modern, web-enabled schemas, and building new databases and front-end tools to manage growing or newly structured data sources.
This is genuine in-house architecture depth, not outsourced work. The same team that designs your database structure builds the applications and reporting tools that sit on top of it, so the two are designed to work together from day one, not bolted together after the fact.
/ Platform capabilities
Database Design & Architecture
- Normalised, scalable schema design for new systems
- Redesign of existing schemas that have outgrown their original structure
- Data modelling that reflects how your business actually relates its information
Legacy Migration
- Migration off ageing, unsupported database environments
- Data integrity validation throughout the migration process
- Minimal-disruption cutover planning
Database platforms
- SQL Server · PostgreSQL · MariaDB · MySQL · MongoDB · Couchbase
Spreadsheet-to-Database Migration
- Structured database replacement for business-critical spreadsheet systems
- Front-end tools that make the data usable, not just stored
- Reduced risk from single-point-of-failure spreadsheet files
Reporting & Front-End Tools
- Front-end interfaces designed alongside the database, not after it
- Reporting tools built for the queries your business actually runs
- Performance tuning for databases under real reporting load
/ Built for B2B and B2C
New System Architecture
Purpose-built schema design for platforms, portals and applications built from the ground up.
Legacy Database Migration
Structured migration off ageing, unsupported systems into a modern, well-documented architecture.
Reporting & Business Intelligence
Database structures designed specifically to support fast, accurate reporting, not adapted for it after the fact.
/ FAQ
The risk usually shows up gradually rather than all at once: performance degrades as data grows, the original vendor or platform stops receiving updates, and fewer people understand how the system actually works as staff move on. The real danger is that by the time it becomes an emergency, migrating under pressure is far riskier than migrating on your own timeline.
This comes down to validation at every stage, not just at the end. We typically run the old and new systems in parallel for a period, comparing outputs to confirm the migrated data matches, and we map every existing report to its new data source before cutover rather than discovering a broken report after go-live.
A relational database, like SQL Server or PostgreSQL, stores data in structured tables with defined relationships between them, which suits data that's consistent and predictable, like customer orders or financial records. A NoSQL database like MongoDB stores more flexible, document-based data, which suits information that varies in structure from one record to the next, like varied product attributes across different categories.
Spreadsheets don't enforce data consistency, don't handle multiple simultaneous users well, and have no real audit trail of who changed what and when. They're genuinely useful for small, simple tasks, but once a spreadsheet becomes the system a business actually runs on, a single corrupted file or version conflict can cause real damage.
This needs proper diagnosis rather than guesswork, usually by examining query execution plans and where time is actually being spent. Often it's a database indexing issue that looks like an application problem, or an application making far more database calls than it needs to. We investigate before recommending a fix, rather than assuming either side is automatically at fault.
In most cases, yes, particularly with careful planning around read replicas, staged migrations or maintenance windows scheduled outside business hours. A full outage is sometimes unavoidable for smaller systems, but for anything business-critical we plan specifically to minimise or eliminate downtime.
Regular performance monitoring, index maintenance as data volumes grow, and periodic review as your reporting needs evolve. A database that was perfectly tuned at launch can slow down over time simply because the data and how it's queried have changed, so we treat this as an ongoing relationship rather than a one-off build.
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