Codebold IT Solutions · PostgreSQL Development
PostgreSQL earns its reputation on data integrity and advanced features — JSONB for flexible fields, full-text search, window functions, strict constraint enforcement — but those features only help if the schema is designed to use them well. We model data with the right balance of normalization and flexibility, and set up connection pooling and vacuum strategy so the database stays healthy under real load.
— What you get
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Data modeled with real normalization where it matters and JSONB where flexibility genuinely earns its place — not one extreme or the other by default.
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Partial and composite indexes used where they actually speed up the queries your app runs, not a blanket index on every column.
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Data integrity rules enforced by PostgreSQL itself, not just hoped for in application code that might have a bug someday.
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PgBouncer or an equivalent configured correctly, so the database doesn't choke under a burst of concurrent connections.
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Autovacuum tuned rather than left on defaults, so bloat doesn't quietly degrade performance months after launch.
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PostgreSQL's built-in search used where it's genuinely sufficient, avoiding the operational cost of standing up Elasticsearch for a problem that doesn't need it.
— How PostgreSQL keeps queries fast and data consistent
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The planner evaluates multiple possible execution strategies for your query and picks the one it estimates will cost the least — that estimate is only as good as the statistics behind it.
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Indexes speed up lookups so PostgreSQL doesn't scan every row, while constraints enforce data integrity at the database level — rejecting bad data before it's ever written.
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Multi-version concurrency control lets reads and writes happen simultaneously without locking each other out — a reader never blocks a writer, and vice versa.
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Background processes reclaim space left behind by updates and deletes and keep query-planner statistics fresh, so performance stays consistent months after launch, not just on day one.
— Why Codebold
Building software since 2013.
JSONB, full-text search, window functions, strict constraints — used deliberately where they solve a real problem, not left unused while we treat it like a generic SQL database.
So the database stays healthy under sustained write load, not just in a demo with five test records.
Fixes, updates, and the next feature are part of the relationship — not a renegotiation every time something needs to change.
— Tech depth
— Good questions
PostgreSQL earns its place when you need advanced features — JSONB, full-text search, strict data integrity, window functions for reporting. For a simpler, well-understood default, MySQL is often the more familiar choice. We'll recommend based on your actual data needs.
Yes — usually starting with EXPLAIN ANALYZE on the actual slow queries, checking index usage and vacuum health, before touching the schema.
For most applications, PostgreSQL's built-in full-text search is genuinely enough, and it avoids the operational overhead of running a separate search service. We'll tell you honestly if your use case has actually outgrown it.
Yes — the schema, migrations, and everything in the repository are yours from day one.
We stay on. Fixes, updates, and the next feature are part of the relationship, not a separate negotiation.
Depends on how much data has to migrate and how many parts of the app touch it. You'll get a clear timeline after we review the current schema.
— Let's talk
Tell us what you're building — we respond to every enquiry within 24 hours, with next steps, not a sales pitch.
Working with clients internationally, since 2013.
