PostgreSQL Architecture Explained: A Deep Dive into How PostgreSQL Works

PostgreSQL is one of the the most advanced and widely used open-source relational database management systems (RDBMS). Known for its robustness, extensibility, and compliance with SQL standards, PostgreSQL powers everything from small applications to large enterprise systems.

To truly harness its power, it’s essential to understand PostgreSQL’s architecture. In this blog, we’ll break down its components, processes, and how they work together to manage data efficiently.

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1. PostgreSQL Architecture Overview

PostgreSQL follows a client-server, process-based model where multiple processes handle different tasks. The architecture consists of:

1. Client Applications (Frontend)

2. PostgreSQL Server Processes (Backend)

   • Postmaster (Main Daemon Process)

   • Backend Processes (per client connection)

   • Background Processes (for maintenance & optimization)

3. Shared Memory (for inter-process communication)

4. Storage Layer (Data Files, WAL, etc.)

Let’s explore each in detail.

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2. PostgreSQL Server Processes

A. Postmaster (Main Daemon Process)

• The first process started when PostgreSQL launches (postgres executable).

• Listens for client connections on a specified port (default: 5432).

• Spawns a new backend process for each client connection (fork-based or thread-based, depending on OS).

• Manages shared memory and coordinates between processes.

B. Backend Processes (One per Client Connection)

• Each client (application, user, or service) connects to PostgreSQL via a dedicated backend process.

• Handles query parsing, optimization, execution, and result return.

• Uses shared buffers for caching data blocks.

C. Background Processes (Maintenance & Optimization)

PostgreSQL runs several background processes for performance and reliability:

Process	Role
Writer (BgWriter)	Flushes dirty buffers from shared memory to disk.
Checkpointer (CKPT)	Triggers checkpoints (periodic sync of data to disk).
WAL Writer (WAL Writer)	Writes Write-Ahead Log (WAL) records to disk for crash recovery.
Autovacuum (AV)	Automatically cleans up dead rows and optimizes tables.
Stats Collector	Gathers database usage statistics for the query planner.
Logger (SysLogger)	Logs server messages to files.

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3. Shared Memory Components

PostgreSQL uses shared memory for inter-process communication and caching:

Component	Purpose
Shared Buffers	Caches frequently accessed data blocks to reduce disk I/O.
WAL Buffers	Temporary storage for WAL records before writing to disk.
Lock Space	Manages locks (row-level, table-level) for concurrency control.
CLOG Buffers	Tracks transaction commit status (committed/aborted).

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4. Storage Layer: How Data is Stored

PostgreSQL stores data in a structured directory (usually PGDATA/base). Key components:

A. Data Files (Heap & Indexes)

• Tables are stored as heap files (unordered data blocks).

• Indexes (B-tree, Hash, GIN, etc.) speed up queries.

B. Write-Ahead Logging (WAL)

• Ensures durability by logging changes before applying them.

• Used for crash recovery & replication (Streaming/WAL Shipping).

C. Transaction Log (pg_xact)

• Tracks transaction status (committed/rolled back).

D. Temporary Files

• Used for large sorts, joins, and temporary tables.

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5. Query Processing Workflow

When a client executes a query, PostgreSQL follows these steps:

1. Connection Handling

   • Client connects → Postmaster spawns a backend process.

2. Parsing

   • SQL query → Parse tree (checks syntax).

3. Rewriting

   • Applies rules (views, triggers).

4. Planning & Optimization

   • Query planner selects the best execution path (cost-based).

5. Execution

   • Executor processes the plan, fetches data, and returns results.

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6. PostgreSQL vs. Other Databases (Architecture Comparison)

Feature	PostgreSQL	MySQL	Oracle
Concurrency	MVCC (Multi-Version Concurrency Control)	Row-level locks	MVCC + Advanced locking
Replication	Built-in (Streaming, Logical)	Async/Semi-sync	Oracle Data Guard
Extensions	Highly extensible (JSON, GIS, Custom Types)	Limited plugins	Proprietary extensions
Process Model	Process-per-connection	Thread-per-connection	Hybrid (Process + Threads)

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7. Conclusion

PostgreSQL’s architecture is designed for scalability, reliability, and performance. Key takeaways:
✅ Multi-process model ensures isolation and stability.
✅ Shared memory optimizes performance by reducing disk I/O.
✅ WAL & Checkpoints ensure data durability.
✅ Background processes automate maintenance (vacuum, stats).

Understanding these internals helps in tuning performance, debugging issues, and scaling PostgreSQL effectively.