PostgreSQL development in Kolkata

+91 94329 43298 WhatsApp

PostgreSQL development

The relational database we default to when data integrity and complex querying both matter.

Relational database

Chosen per project

Maintainable handover

PostgreSQL is the sensible default for business systems. It enforces constraints properly, handles concurrent transactions correctly, and supports the kind of analytical queries that would otherwise require a separate reporting system.

Most database problems we are asked to fix are not database problems at all — they are missing indexes, unbounded queries and a schema that never anticipated the reports now being run against it.

What we build with PostgreSQL

Transactional business systems where correctness is non-negotiable

Reporting and analytics alongside operational data

Multi-tenant applications using schema-level isolation

Systems mixing relational data with JSON documents

Where it fits — and where it does not

Good fit when

Data with genuine relationships and integrity requirements

Complex queries, aggregation and reporting

Transactional correctness under concurrency

A mix of structured and semi-structured data

Consider something else when

Very high write throughput of unstructured events

Simple key-value caching, better served by Redis

Teams with no SQL capability and no intention of acquiring any

Query performance

How we make a slow query fast

The order matters. Most performance work is finished by step three; reaching for more hardware first is how organisations spend money without fixing anything.

Measure

Find the queries actually consuming time, using statistics rather than intuition.

Read the plan

Examine the execution plan to see what the planner is really doing.

Index

Add or correct indexes, including partial and composite ones.

Rewrite

Restructure the query, or the access pattern that produced it.

Denormalise

Materialised views or summary tables, where the read pattern justifies it.

Scale

Read replicas or more capacity — last, once the above is exhausted.

How we work with PostgreSQL

Schema design

Normalised where it protects integrity, denormalised deliberately where reads demand it.

Indexing

Indexes chosen from the queries that will actually run, then verified against query plans.

Migrations

Versioned, reversible and tested against production-sized data before release.

Backup and recovery

Point-in-time recovery configured, and restores actually rehearsed.

Our typical PostgreSQL setup

Typical PostgreSQL stack choices and what we use for each
ConcernWhat we use
VersionA currently supported PostgreSQL major release
MigrationsVersioned and reversible, applied through the deployment pipeline
IndexingB-tree, partial, composite and GIN indexes as the queries require
ExtensionsPostGIS, pg_trgm and others where the problem calls for them
BackupAutomated snapshots plus point-in-time recovery, restores tested
MonitoringSlow query logging and connection pool metrics

Frequently asked questions

PostgreSQL for stricter data integrity, richer query capability and better handling of complex or semi-structured data. MySQL remains a reasonable choice for simpler read-heavy applications and is more widely available on inexpensive shared hosting.

Almost always, and usually without new hardware. The common causes are missing indexes, queries fetching far more than they need, and reports run against the live transactional tables.

Yes, with indexing and querying support for JSONB. That makes it a practical single database for systems that are mostly relational but have some flexible document data.

Topics people search for

Services built with PostgreSQL

Tell us what you are trying to build

Describe the problem in plain language and we will tell you what it would take to solve it — the approach, the moving parts and the sensible order to build them in. No obligation either way.

WhatsApp
Call now Enquire