Modern applications depend on databases for performance, reliability, and growth. As systems scale, you inevitably face challenges: failovers, traffic spikes, migrations, read/write bottlenecks, and the need for flexibility across environments.
pgcat is a PostgreSQL proxy that sits transparently between your application and your databases. It allows organizations to introduce reliability, scalability, and operational flexibility without requiring application changes.
This document explains what pgcat solves, when to use it, and its business value in a way suitable for executives and decision makers.
p gcat acts as a smart traffic controller for PostgreSQL. Instead of your application connecting directly to databases, it connects to pgcat. pgcat then decides where each request should go based on rules, availability, and efficiency.
Key idea: your app continues working the same way, but your database environment becomes more flexible, scalable, and fault‑tolerant.
When a primary database fails, applications usually break. pgcat detects failures and automatically redirects traffic to a healthy replica.
Outcome: fewer outages, lower incident cost, improved SLAs.
Changing from on‑prem to cloud, upgrading versions, or replacing components often requires rewriting application logic.
pgcat provides an abstraction layer so backend changes stay invisible to applications.
Outcome: technology flexibility, easier modernization, lower migration effort.
Large migrations are risky. pgcat helps orchestrate gradual cutovers:
Move certain tenants/users first
Route a percentage of traffic to a new cluster
Test new environments without committing
Outcome: reduced migration risk, ability to migrate with zero or minimal downtime.
Most applications cannot distinguish between read and write queries. pgcat does this automatically:
Writes → primary
Reads → replicas
Outcome: immediate performance improvements without engineering cost.
pgcat can cache frequently used read queries.
Outcome: faster reads, reduced database costs, better performance during traffic peaks.
When a single database can no longer handle the load, systems must shard data.
pgcat supports rule‑based sharding, letting businesses scale without application redesign.
Outcome: long‑term scalability without rewriting core business systems.
PostgreSQL consumes significant memory for each client connection. pgcat reduces the number of open connections and stabilizes traffic.
Outcome: lower infrastructure costs and improved database stability.
pgcat inserts a lightweight control layer between the app and your databases. It:
Receives connections from applications.
Understands the type of request (read, write, cached read, shard‑specific, etc.).
Routes requests to the appropriate database instance.
Manages failovers, ensures health, and avoids broken connections.
Pools and reuses connections to optimize resource consumption.
No application code is changed.
No migration to a new client library.
No major operational overhead.
This makes pgcat a strategic infrastructure component that enables flexibility, modernization, and resilience.
Automatic failover and intelligent routing mean fewer production incidents and lower SLA penalties.
Teams can switch underlying architectures (cloud/on‑prem, PG version upgrades) without waiting for long development cycles.
Connection pooling + caching reduce load on primary infrastructure.
Increasing read throughput or scaling out replicas becomes immediate.
pgcat supports scaling from a single database to many clusters and shards.
pgcat itself is lightweight and open‑source. Costs relate to supporting infrastructure.
Reduced need to scale database instances due to pooling and caching
Avoids expensive downtime (especially P1 incidents)
Reduces engineering effort on migrations and rewrites
Delays significant redesign costs by enabling sharding later
Requires running pgcat nodes (typically 2–3 small instances or pods)
Requires minimal operational monitoring
Adds a new infrastructure component (small complexity overhead)
In most cases, the benefits outweigh the operational cost.
If misconfigured, pgcat can become a bottleneck.
Mitigation: run pgcat as a redundant, highly available set.
If read/write rules or sharding strategies are incorrectly defined, routing may behave unexpectedly.
Mitigation: governance, testing, and phased rollout.
Requires adding pgcat to monitoring, logging, and operational checklists.
Mitigation: standardize dashboards, alerts, and testing.
Choose pgcat when you:
Need failover protection without redesigning applications
Plan migrations or major database upgrades
Want read/write splitting without touching code
Need sharding or tenant isolation
Want better performance without scaling hardware
Operate multi‑tenant environments
Want flexibility in how you structure and evolve your data layer
pgcat is ideal for modern, growing products where the database layer must evolve without application disruption.
p gcat provides a strategic database abstraction layer that enables reliability, performance, flexibility, and modernization. It reduces engineering effort, operational risk, and infrastructure cost—while offering a clean path for future growth.
For organizations aiming to scale, modernize, or simply gain more control over their PostgreSQL environments, pgcat is a practical and cost‑efficient choice.