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Backend & Infrastructure

Data Architecture That Doesn't Come Back to Haunt You

Schema design, query optimisation, Redis caching, and zero-downtime migrations for applications that need to scale. Getting the data model right from day one.

Timeline 1–3 weeks
Investment $1,500–$5,000
PostgreSQLRedisDjango ORMDockerpgAdminNginx
📐
Schema design

Normalised database schema with proper relationships, constraints, and indexing strategy.

Query optimisation

Slow query analysis, index tuning, and ORM query review — measurable performance improvements.

💾
Redis caching layer

Cache strategy for expensive queries and session data. Significant response time reduction.

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Migration plan

Safe, reversible migrations from existing schema — zero data loss, minimal downtime.

01
Audit existing schema

Review current tables, relationships, and query patterns. Identify bottlenecks and structural problems.

02
Schema redesign

New or refactored schema with proper normalisation, foreign keys, and index strategy documented.

03
Migration implementation

Django migration files or raw SQL — tested on a copy of production data before running live.

04
Caching & monitoring

Redis setup for hot data, query logging enabled, and performance baseline documented.

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PostgreSQL handles everything, but Redis is faster for frequently-read data that rarely changes — session tokens, cached API responses, leaderboards. If your app is slow on reads, Redis is usually the fix.
Yes — slow query analysis is usually the fastest win. Often a missing index or an N+1 query is the culprit. I'll find it and fix it.
I prefer PostgreSQL for production — it's more capable and reliable. SQLite is fine for development and small internal tools. I can work with MySQL if it's already in your stack.
I'll set up automated PostgreSQL backups (pg_dump) and document the restore procedure. Disaster recovery planning included.
Yes — zero-downtime migration strategies for live applications. Multi-step migrations when a direct change would lock tables.
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