Database Management

PostgreSQL Performance Tuning Guide Topical Map

Complete topic cluster & semantic SEO content plan — 35 articles, 6 content groups  · 

Build a comprehensive topical hub that covers fundamentals, configuration, query optimization, maintenance, scaling, and tooling for PostgreSQL performance. The collection will provide authoritative, actionable reference material — from baseline metrics and monitoring to deep-dive tuning, benchmarking, and troubleshooting — positioning the site as the go-to resource for DBAs and engineers solving real-world Postgres performance problems.

35 Total Articles
6 Content Groups
21 High Priority
~6 months Est. Timeline

This is a free topical map for PostgreSQL Performance Tuning Guide. A topical map is a complete topic cluster and semantic SEO strategy that shows every article a site needs to publish to achieve topical authority on a subject in Google. This map contains 35 article titles organised into 6 topic clusters, each with a pillar page and supporting cluster articles — prioritised by search impact and mapped to exact target queries.

How to use this topical map for PostgreSQL Performance Tuning Guide: Start with the pillar page, then publish the 21 high-priority cluster articles in writing order. Each of the 6 topic clusters covers a distinct angle of PostgreSQL Performance Tuning Guide — together they give Google complete hub-and-spoke coverage of the subject, which is the foundation of topical authority and sustained organic rankings.

📋 Content Plan 📚 Full Library 📊 Strategy

📋 Your Content Plan — Start Here

35 prioritized articles with target queries and writing sequence.

High Medium Low
1

Fundamentals & Monitoring

Covers the essential metrics, baselining and monitoring practices every DBA needs before making changes. Establishing correct baselines and understanding wait events prevents misdiagnosis and provides context for tuning.

PILLAR Publish first in this group
Informational 📄 3,500 words 🔍 “postgresql performance baseline”

PostgreSQL Performance Fundamentals: Key Metrics, Baselines, and Monitoring

This pillar explains core Postgres performance concepts, the metrics that matter, and how to establish reliable baselines. Readers learn where to collect metrics (pg_stat views, OS tools), how to interpret wait events and planner activity, and how to set up monitoring and alerting that support safe tuning decisions.

Sections covered
Performance concepts: MVCC, planner vs executor, and typical bottlenecks Key Postgres metrics and views (pg_stat_activity, pg_stat_database, pg_stat_statements) Establishing baselines and repeatable benchmarks Monitoring stacks: Prometheus, Grafana, and managed monitoring (RDS/Cloud SQL) Interpreting wait events and top symptoms (I/O, CPU, locks, bloat) Setting meaningful alerts and SLA thresholds
1
High Informational 📄 1,200 words

How to establish a PostgreSQL performance baseline with pgbench and real traffic

Step-by-step guide to create repeatable baselines using pgbench and how to capture representative production-like workloads for valid comparisons.

🎯 “postgresql performance baseline with pgbench”
2
High Informational 📄 1,000 words

Essential PostgreSQL metrics to monitor (pg_stat and OS-level)

Catalog of the critical Postgres and OS metrics to track, why they matter, and recommended thresholds for alerting.

🎯 “postgresql metrics to monitor”
3
High Informational 📄 1,400 words

Using pg_stat_statements: find the queries that cost you the most

How to install, interpret and act on pg_stat_statements data, including normalization, grouping and integration with dashboards.

🎯 “pg_stat_statements tutorial”
4
Medium Informational 📄 1,400 words

Set up Prometheus + Grafana for PostgreSQL monitoring

Practical walkthrough: exporters, key dashboard panels, common alerts, and mapping Postgres metrics to operational questions.

🎯 “prometheus grafana postgresql monitoring”
5
Medium Informational 📄 1,100 words

Interpreting Postgres wait events and resolving common symptoms

Explain common wait events, how to locate their root causes, and triage steps for I/O, CPU, and lock-related waits.

🎯 “postgres wait events explained”
2

Configuration & System Resources

Deep coverage of Postgres configuration and OS/ hardware settings — memory, WAL, checkpoints, and kernel tuning — to align database behavior with workload and hardware.

PILLAR Publish first in this group
Informational 📄 4,500 words 🔍 “postgresql configuration tuning”

Tuning PostgreSQL Configuration and System Resources for Performance

An authoritative guide to the configuration knobs and system-level choices that most affect Postgres performance. Covers memory, WAL/checkpoint behavior, autovacuum defaults, I/O settings, and kernel parameters, plus example configurations for common workloads.

Sections covered
Memory settings: shared_buffers, work_mem, maintenance_work_mem WAL, checkpoints and durability trade-offs (wal_buffers, checkpoint_timeout, synchronous_commit) Autovacuum configuration and table-specific settings Planner and parallelism parameters (effective_cache_size, max_worker_processes, max_parallel_workers) OS and filesystem tuning: IO schedulers, dirty ratios, hugepages, and filesystems Storage and hardware choices: SSD/NVMe, RAID, and network storage Example tuned configs for OLTP, OLAP and mixed workloads
1
High Informational 📄 900 words

How to size and set shared_buffers in PostgreSQL

Guidelines and experiments to find an appropriate shared_buffers value for your workload and hardware, with examples and pitfalls.

🎯 “how to set shared_buffers”
2
High Informational 📄 1,000 words

Tuning work_mem and maintenance_work_mem for query performance

Explain how work_mem affects sorts and hash operations, strategies for per-session vs per-query calculation, and safe defaults.

🎯 “tune work_mem postgresql”
3
High Informational 📄 1,200 words

WAL and checkpoint tuning: reduce write stalls and checkpoint spikes

How WAL settings and checkpoint behaviour interact with IO patterns, and practical tuning steps to avoid long pauses and throughput drops.

🎯 “postgres checkpoint tuning”
4
Medium Informational 📄 1,300 words

OS kernel and filesystem tuning for PostgreSQL performance

Recommended kernel parameters, filesystem choices and I/O scheduler settings that impact Postgres, with commands and configuration examples.

🎯 “kernel tuning postgresql”
5
Low Informational 📄 800 words

Using pgTune and configuration templates safely

How to use tools like pgTune as a starting point and adapt their recommendations to real-world workloads and monitoring feedback.

🎯 “pgtune postgres”
3

Query Optimization & Indexing

Focused, in-depth guidance on writing efficient SQL, choosing and designing indexes, and using planner insights to improve execution plans and latency.

PILLAR Publish first in this group
Informational 📄 5,000 words 🔍 “postgresql query optimization”

Query Optimization and Indexing Strategies in PostgreSQL

The definitive guide to understanding the Postgres planner and creating query- and index-level improvements that materially reduce latency and resource use. It walks through EXPLAIN analysis, index selection and design patterns for joins, aggregates, partial/functional indexes, and partition-aware indexing.

Sections covered
How the planner uses statistics: ANALYZE, stats targets, and common pitfalls EXPLAIN and EXPLAIN ANALYZE: reading plans and spotting cardinality errors Index types and when to use them (btree, gin, gist, brin, hash) SQL anti-patterns and rewrites that improve plans Join strategies, statistics-driven decisions and reordering Partial, expression and covering indexes Partitioning effects on planning and indexing
1
High Informational 📄 1,800 words

Mastering EXPLAIN and EXPLAIN ANALYZE in PostgreSQL

A tactical guide to interpreting EXPLAIN output, diagnosing cardinality estimation errors, and actionable steps to fix bad plans.

🎯 “explain analyze postgresql tutorial”
2
High Informational 📄 1,500 words

Choosing the right index type: btree, GIN, GiST, BRIN and hash

Compare index types with real-world examples, pros/cons, storage and maintenance trade-offs, and performance impact.

🎯 “postgres index types explained”
3
High Informational 📄 1,600 words

SQL anti-patterns that kill Postgres performance (and how to rewrite them)

Identify common inefficient SQL patterns (functions on columns, non-sargable predicates, unbounded JOINs) and provide optimized rewrites with benchmarks.

🎯 “postgres sql anti-patterns”
4
Medium Informational 📄 1,200 words

Partial, expression and covering indexes: advanced patterns

When to use partial and expression indexes to reduce index size and improve specific query performance, with examples and maintenance notes.

🎯 “partial index postgresql examples”
5
Medium Informational 📄 1,600 words

Partitioning: strategies that speed queries and simplify maintenance

Partitioning types, planning for partition pruning, index placement, and when partitioning improves query performance vs when it doesn't.

🎯 “postgres partitioning strategies”
4

Vacuum, Bloat & Maintenance

Explain MVCC consequences and practical maintenance: autovacuum tuning, detecting and fixing bloat, and scheduling operations safely to avoid production impact.

PILLAR Publish first in this group
Informational 📄 3,500 words 🔍 “postgres vacuum bloat management”

Vacuuming, Bloat Management, and Routine Maintenance for PostgreSQL

Comprehensive coverage of MVCC-driven bloat, autovacuum internals, and the tools/techniques to detect, prevent and repair bloat without jeopardizing uptime. It explains autovacuum tuning, manual vacuum strategies, and utilities like pg_repack.

Sections covered
Why bloat happens: MVCC, dead tuples and visibility maps Autovacuum internals and how to tune thresholds and cost limits Detecting bloat with queries and tools (pgstattuple, pg_freespacemap) Repairing bloat: VACUUM, VACUUM FULL, pg_repack and row-level options Maintenance windows and running heavy operations safely Table-level settings and autovacuum tuning for critical tables
1
High Informational 📄 1,400 words

Tuning autovacuum for large and busy tables

How to adjust autovacuum scale factors, cost_delay and scheduling to maintain health of large tables without causing IO storms.

🎯 “tune autovacuum postgresql”
2
High Informational 📄 1,000 words

Detecting table and index bloat and calculating reclaimable space

SQL queries and tools to quantify bloat and prioritize remediation work by ROI and operational constraints.

🎯 “detect postgresql bloat”
3
Medium Informational 📄 1,100 words

Using pg_repack and VACUUM FULL safely in production

When to use pg_repack vs VACUUM FULL, step-by-step procedures, locking behaviour and best practices for minimal downtime.

🎯 “pg_repack vs vacuum full”
4
Low Informational 📄 900 words

Maintenance best practices: backups, ANALYZE cadence, and schema migrations

Operational checklist for routine maintenance tasks including backup strategies, frequency of ANALYZE, and safely applying schema changes.

🎯 “postgres maintenance best practices”
5

Scaling & High Concurrency

Strategies and trades for scaling Postgres vertically and horizontally: connection management, pooling, replication, partitioning and designing for high concurrency.

PILLAR Publish first in this group
Informational 📄 4,000 words 🔍 “scale postgresql connections pooling”

Scaling PostgreSQL: Connections, Pooling, Replication, and Partitioning

This pillar covers how to scale PostgreSQL for growth and concurrency while preserving performance. It explains connection pooling, replication modes, partitioning, and architectural patterns to scale reads and writes with examples and operational considerations.

Sections covered
Connection limits and why unbounded connections hurt performance Connection pooling: PgBouncer modes and configuration Replication fundamentals: streaming, synchronous vs asynchronous, and lag considerations Logical replication and Change Data Capture (CDC) for scaling writes Sharding and application-level partitioning strategies Read scaling: load balancing, replicas, and consistency trade-offs Operational concerns: failover, backups, and monitoring replication
1
High Informational 📄 1,400 words

When and how to use PgBouncer: transaction vs session pooling

Explain pool modes, common configuration options, pitfalls with prepared statements, and recommended setups for web apps and pooled workers.

🎯 “pgbouncer transaction pooling vs session pooling”
2
High Informational 📄 1,500 words

Configuring streaming replication for performance and minimal lag

Practical guide to set up streaming replication, tune wal_level and wal_sender settings, monitor replication lag, and plan failover.

🎯 “postgres streaming replication setup”
3
Medium Informational 📄 1,200 words

Logical replication and CDC patterns for scaling and integrations

When to use logical replication or CDC tools, performance considerations, and handling schema changes across replicas.

🎯 “postgres logical replication use cases”
4
Medium Informational 📄 1,200 words

Partitioning strategies for very large tables to improve concurrency

Partitioning design patterns (range, list, hash) that reduce contention and maintenance overhead while supporting high concurrency.

🎯 “postgres partitioning for large tables”
5
Low Informational 📄 800 words

Connection management and max_connections tuning

How to size max_connections appropriately and coordinate it with poolers, RAM, and work_mem to avoid resource exhaustion.

🎯 “tune max_connections postgresql”
6

Benchmarking, Tools & Troubleshooting

Practical tooling and diagnostic workflows for reproducing performance issues, profiling CPU/IO, analyzing logs, and performing postmortem root cause analysis.

PILLAR Publish first in this group
Informational 📄 3,000 words 🔍 “postgresql benchmarking and troubleshooting”

Benchmarking, Profiling, and Troubleshooting PostgreSQL Performance Issues

A hands-on playbook for benchmarking and diagnosing Postgres performance problems. Covers synthetic and production-like benchmarks, log analysis, CPU/IO profiling, query-level sampling, and a prioritized troubleshooting checklist for common symptoms.

Sections covered
Designing benchmarks: pgbench, real workload capture and replay Log configuration and analysis (log_min_duration_statement, pgbadger) Using perf, iostat, and flamegraphs for CPU/IO profiling Finding slow queries: pg_stat_statements, auto_explain and sampling Diagnosing locking, deadlocks and contention (pg_locks, pg_stat_activity) Postmortem process and creating reproducible tests
1
High Informational 📄 1,300 words

How to benchmark PostgreSQL with pgbench and custom workloads

Create deterministic benchmarks using pgbench, scale factors, custom scripts, and how to interpret results across runs.

🎯 “benchmark postgresql with pgbench”
2
High Informational 📄 1,100 words

Analyzing Postgres logs with pgbadger and best log settings

Recommended logging configuration for performance troubleshooting and how to use pgbadger to generate actionable reports.

🎯 “pgbadger tutorial”
3
Medium Informational 📄 1,200 words

Finding and fixing slow queries with auto_explain and sampling

Set up auto_explain, use query sampling strategies and combine with pg_stat_statements to prioritize optimization work.

🎯 “find slow queries postgresql”
4
Medium Informational 📄 1,000 words

Diagnosing locking, deadlocks and contention in PostgreSQL

How to read pg_locks and pg_stat_activity, reproduce locking scenarios, and resolution patterns including application-level fixes.

🎯 “postgres deadlock diagnosis”
5
Low Informational 📄 1,000 words

CPU and I/O profiling for Postgres: perf, iostat and flamegraphs

Collecting and interpreting OS-level profiles to distinguish CPU-bound from IO-bound workloads and find hotspots.

🎯 “postgres perf flamegraph tutorial”

Content Strategy for PostgreSQL Performance Tuning Guide

The recommended SEO content strategy for PostgreSQL Performance Tuning Guide is the hub-and-spoke topical map model: one comprehensive pillar page on PostgreSQL Performance Tuning Guide, supported by 29 cluster articles each targeting a specific sub-topic. This gives Google the complete hub-and-spoke coverage it needs to rank your site as a topical authority on PostgreSQL Performance Tuning Guide — and tells it exactly which article is the definitive resource.

35

Articles in plan

6

Content groups

21

High-priority articles

~6 months

Est. time to authority

What to Write About PostgreSQL Performance Tuning Guide: Complete Article Index

Every blog post idea and article title in this PostgreSQL Performance Tuning Guide topical map — 0+ articles covering every angle for complete topical authority. Use this as your PostgreSQL Performance Tuning Guide content plan: write in the order shown, starting with the pillar page.

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This topical map is part of IBH's Content Intelligence Library — built from insights across 100,000+ articles published by 25,000+ authors on IndiBlogHub since 2017.

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