What we do
Database schema design for new applications, query optimization for existing systems, migration planning between database engines, and data pipeline development for analytics and reporting.
Deliverables
- Entity-relationship diagram (ERD)
- Schema with versioned migrations
- Query optimization report (before/after benchmarks)
- Data pipeline (if applicable)
- Indexing strategy document
Scope examples
- New application schema: Design normalized schema, write migrations, set up indexing strategy, configure connection pooling.
- Performance optimization: Profile slow queries, add indexes, rewrite N+1 patterns, implement caching layer.
- Migration: Plan and execute migration between database engines (e.g., MySQL → PostgreSQL) with data validation.
- Data pipelines: ETL/ELT pipelines from operational databases to analytics warehouses.
Tech stack defaults
- RDBMS: PostgreSQL
- Document store: MongoDB or DynamoDB
- Cache: Redis
- Search: Meilisearch or Elasticsearch
- Vector: pgvector or Qdrant
- Migrations: Drizzle Kit, Alembic, or golang-migrate