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Database architecture your future self will thank you for.

Schemas, indexes, and migrations designed for the product you'll have in two years, not just the demo next week.

IN ONE ANSWER

Dev4ager designs database architectures, schema design, indexing strategy, multi-tenant models, and zero-downtime migrations, for PostgreSQL, MySQL, and MongoDB. We also rescue existing databases: slow queries, tangled schemas, and "please don't touch that table" situations.

What we do

Every feature you'll ever ship sits on top of the data model. Get it roughly right early and everything downstream is easy; get it wrong and every sprint pays interest. We do the getting-it-right , and the un-getting-it-wrong.

  • Schema design mapped from your actual business domain
  • Indexing strategy based on real query patterns, not guesses
  • Multi-tenant models with row-level security
  • Query optimization: EXPLAIN-driven fixes for slow endpoints
  • Zero-downtime migrations (expand-and-contract, batched backfills)
  • Backup, retention, and recovery plans that have actually been tested

How we work

  1. Model the domain. Entities and relationships from how your business actually works.
  2. Design for queries. The schema serves the questions your product asks most.
  3. Review + implement. Migrations as reviewed code, reversible, tested on staging data.
  4. Verify. Query plans and load characteristics checked before and after.

Stack we reach for

PostgreSQL Supabase MySQL MongoDB Prisma SQL views RLS

A great fit if…

  • You're starting a product and want the data model done right the first time.
  • Dashboards take ten seconds to load and nobody knows why.
  • Your schema grew feature-by-feature and now fights every new requirement.

Database architecture FAQs

SQL or NoSQL for our product?

If your entities reference each other, users, orders, subscriptions, relational (PostgreSQL) is almost always right, and it handles JSON fine for the flexible parts. NoSQL earns its place for specific shapes: document stores, caches, event streams. Most products that chose NoSQL "for scale" actually just deferred their schema decisions.

Can you fix our slow queries?

Yes, we profile with EXPLAIN ANALYZE, then fix in order of leverage: missing indexes, N+1 patterns, over-fetching, and only then schema changes. Most "we need a bigger server" situations are actually a missing index. See also performance optimization.

Can you change our schema without downtime?

Yes, expand-and-contract migrations: add the new structure alongside the old, backfill in batches, switch reads, then drop the old. Every step is reversible, which is what makes it boring, the good kind of boring.

How should multi-tenant data be designed?

For most SaaS: one database, tenant_id on every table, enforced by row-level security, cheap to run, easy to query across tenants. Schema-per-tenant or database-per-tenant only when isolation requirements (enterprise, compliance) genuinely demand it. More in SaaS development.

Related

Supabase Backends Performance SaaS Development Guide: Our AI workflow

Data model doubts?

Show us your schema, or the idea that needs one. We'll review it and quote the work.

Review My Data Model