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The database is often the least visible and most critical component of a business application. Poorly designed data models create performance problems that are expensive to fix, data integrity issues that are difficult to diagnose, and migration costs that grow with every additional feature. wecopars brings rigorous database design discipline to every engagement.
We design schemas for correctness first — ensuring that the data model enforces the business rules your application depends on — and then optimise for performance, ensuring that the queries your application runs most frequently execute efficiently at your expected data volumes.
Database Technology Selection
We select database technology based on your specific data access patterns and consistency requirements. PostgreSQL for relational data with complex querying needs; MongoDB for document-oriented workloads with flexible schemas; Redis for caching, session storage, and pub/sub messaging; ClickHouse or TimescaleDB for analytical workloads over time-series data; Elasticsearch for full-text search.
In many production systems, multiple database technologies are used together, each serving the access pattern it is best suited for. We design the data architecture as a whole, ensuring that the different stores are kept consistent and that the boundary between them is clearly defined.
Migration and Optimisation
For existing systems with database performance problems, we conduct a comprehensive analysis: query profiling, index review, schema normalisation assessment, and connection pool configuration. We deliver a prioritised list of improvements with estimated impact, and can implement the changes with the care for zero-downtime migration that production systems require.