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How PostgreSQL Uses Memory (and Why You Should Care)

#PostgreSQL

#PostgreSQLDBA

#DatabasePerformance

#SQL

#PostgreSQLMemory

#DatabaseTuning

#DBA

#PostgreSQLPerformance

#SQLOptimization

#QueryPerformance

#PostgreSQLAdmin

#PostgreSQLTutorial

#MemoryManagement

#DatabaseArchitecture

#DBPerformance

#PostgreSQLOptimization

#PostgreSQLConfig

#PostgreSQLPerformanceTuning

#work_mem

#PostgreSQL15

#PostgreSQLTips

#PostgreSQLBestPractices

#CloudDBA

#DatabaseEngineering

#DBATips

#SQLPerformanceTuning

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Автор: thedbadmin

Загружено: 2025-03-05

Просмотров: 109

Описание: 🚀 Understanding PostgreSQL's Memory Architecture: A Deep Dive!

PostgreSQL is one of the most powerful relational databases, and understanding its memory architecture is crucial for database administrators, developers, and performance tuners.

In this video, we explore PostgreSQL's memory management system, breaking it down into:

✅ Local Memory Area – How individual backend processes allocate memory
✅ Shared Memory Area – How memory is shared across all PostgreSQL processes
✅ Dynamic Shared Memory (DSM) – Used for parallel query execution and extensions like logical replication
✅ Key PostgreSQL memory parameters – work_mem, maintenance_work_mem, temp_buffers, and more

📌 Why Does Memory Architecture Matter?
Efficient memory allocation in PostgreSQL directly impacts:
⚡ Query performance – Optimizing work_mem can improve sorting and joins
⚡ Maintenance operations – Fine-tuning maintenance_work_mem enhances VACUUM and REINDEX efficiency
⚡ Concurrency and reliability – Proper WAL buffer and commit log tuning ensure safe transactions

📌 Whether you're a PostgreSQL DBA, developer, or a database enthusiast, this video will help you master PostgreSQL's memory architecture!

💡 Want More PostgreSQL Performance Tuning Tips?
Make sure to LIKE, SUBSCRIBE, and turn on NOTIFICATIONS 🔔 so you don't miss out on more PostgreSQL tutorials, database optimization techniques, and AI-powered database administration-only on TheDBAdmin.com!

🗨️ Have questions or PostgreSQL performance issues? Drop a comment below!

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How PostgreSQL Uses Memory (and Why You Should Care)

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