Database development that your data can grow on.

It's the design and engineering of the data layer your software runs on: modeling your entities into a schema, choosing the right database, writing and optimizing queries, setting up indexes, applying safe migrations, enforcing data integrity, and putting backups and recovery in place. In short, making sure your data is structured well, fast to access, and safe.

It depends on your data and how you use it. Relational databases like PostgreSQL are the right default for most applications: they enforce integrity and handle complex queries well. NoSQL fits specific needs, like very high write volume, flexible documents, or particular access patterns. We choose based on your requirements rather than a preference, and often a relational core with a cache or document store for the parts that need it.

Mostly through good design and the right indexes. We model the schema around your real access patterns, add indexes to the queries that need them, and rewrite the slow ones, then use caching and connection pooling to take load off the database. We measure with real query plans at expected volume, so speed comes from evidence, not guesswork.

Yes. We audit the current schema, queries, and indexes, find where integrity or performance is breaking down, and design a path to a better structure. Because a database is rarely something you can replace overnight, we do it through incremental, reversible migrations that improve it step by step without a risky big-bang rewrite.

With versioned, reversible migrations, tested against a copy of real data before they touch production, and applied in a controlled sequence. For larger changes we use techniques like backfilling and dual-writes so the switch is gradual, and we always have a backup and a rollback plan, so a migration is a routine step rather than a gamble.

We set up automated backups and actually test recovery, so a restore works when you need it rather than only in theory. We enforce integrity with constraints and transactions, keep access least-privilege, and add replication where availability matters. The goal is that a mistake, bug, or failure is recoverable, not catastrophic.