What Are HOT Tuples in PostgreSQL? A Complete Guide for DBAs

PostgreSQL’s architecture is full of smart engineering decisions, and one of the most impactful—yet often overlooked—is the HOT (Heap-Only Tuple) update mechanism. If you work with write-heavy systems, high-traffic applications, or platforms like Odoo/ERP/CRM that frequently modify rows, understanding HOT tuples can drastically improve database performance.

This article provides a structured and comprehensive examination of HOT tuples, exploring what they are, how they function, when they are applicable, and how you can optimize your schema to leverage their full potential.

Overview

• PostgreSQL never overwrites existing rows.
• Every update creates a new version of the row.
• HOT updates allow PostgreSQL to avoid unnecessary index changes.
• This reduces index bloat and improves update throughput significantly.

How PostgreSQL Stores Rows

In PostgreSQL terminology, a row is called a tuple, and every tuple is stored inside a fixed-size data page (usually 8 KB). Each tuple contains:

• CTID: A physical pointer to its location ((page_id, tuple_id)).
• Transaction metadata: Visibility information (xmin, xmax).
• The actual column data.

This storage structure is foundational for PostgreSQL’s MVCC (Multi-Version Concurrency Control) model.

Why Updates Create New Tuples

PostgreSQL uses MVCC to allow concurrent reading and writing without locking. Under MVCC:

• Updates do not modify a row in-place.
• Instead, PostgreSQL inserts a new version of the row.
• The old version remains in the page until it is no longer visible to any running transaction.
• The visibility chain is maintained through t_ctid.

This behavior ensures consistency and isolation but traditionally comes at a cost: index bloat.

The Problem: Index Bloat from Updates

Before HOT existed, every update forced PostgreSQL to:

1. Create a new tuple version.
2. Insert a new index entry for that new version.
3. Keep old index entries alive until VACUUM cleans them.

In high-update environments, this resulted in:

• Larger indexes
• Higher I/O costs
• Slower queries
• More frequent VACUUM activity
• Increased storage consumption

What Are HOT Tuples?

HOT stands for Heap-Only Tuple. Introduced in PostgreSQL 8.3, HOT was designed to optimize the update process.

A HOT update occurs when:

1. The updated row can be placed in the same heap page as the original.
2. The update does not modify any indexed column.

When both conditions are met:

• PostgreSQL creates a new tuple version on the same page.
• No new index entry is created.
• Existing index entries still point to the original tuple.
• PostgreSQL internally follows the chain to the latest version.

This results in a fast, space-efficient update operation.

How HOT Updates Work Internally

Imagine a row stored at CTID (5,2). You update a non-indexed column:

UPDATE users SET status = 'active' WHERE id = 1;

PostgreSQL performs:

• A new version of the tuple is created on the same page, say (5,7).
• The original tuple at (5,2) now points to (5,7).
• Index still points to (5,2).

The chain looks like:

(5,2)  ?  (5,7)

During a SELECT:

• PostgreSQL fetches the tuple using the index.
• Sees that (5,2) is not the visible version.
• Follow the chain to (5,7).

This is extremely efficient and requires no index maintenance.

Benefits of HOT Updates

1. Reduced Index Bloat

No new index entries are created.

Indexes stay smaller and faster.

2. Improved Update Performance

Updating non-indexed columns becomes significantly quicker.

3. Better Autovacuum Behavior

With fewer stale index entries:

• Autovacuum runs faster.
• Autovacuum is triggered less often.
• VACUUM does not have to clean up index bloat.

4. Lower Storage Consumption

Heap pages and indexes grow more slowly.

When HOT cannot be used

HOT is not always possible. It will not occur when:

• You update an indexed column.
• There is not enough free space in the data page.
• The row contains a large TOASTed value and must be moved.
• The data page is fragmented or heavily packed (high fill factor).
• A previous update chain is too long or blocked by dead tuples.

In these cases, PostgreSQL performs a regular update, including index changes.

Monitoring HOT Updates

PostgreSQL provides statistics in pg_stat_user_tables:

SELECT relname, n_tup_hot_upd, n_tup_upd
FROM pg_stat_user_tables;

• n_tup_hot_upd > number of HOT updates
• n_tup_upd > total updates

A high ratio of HOT updates to total updates is desirable.

To inspect the actual page contents, extensions like pageinspect help:

SELECT * FROM heap_page_items(get_raw_page('users', 0));

Real-World Use Case

In business applications like Odoo/ERP, common fields such as:

• state
• write_date
• last_sync
• status
• description

Often updated frequently, but are normally not indexed. This makes them perfect candidates for HOT updates.

With HOT:

• Write throughput increases significantly
• The database remains responsive during heavy load
• The storage footprint grows more slowly over time

How to Increase HOT Update Occurrence

1. Avoid indexing columns that change frequently

Do not index fields that are updated often, unless absolutely required.

2. Adjust fillfactor

Leave extra space in pages to accommodate HOT chains:

ALTER TABLE users SET (fillfactor = 70);

Then:

VACUUM FULL users;

3. Maintain healthy vacuuming

Tuning autovacuum prevents page fragmentation, increasing chances for HOT.

Conclusion

HOT tuples are a powerful performance optimization inside PostgreSQL’s MVCC engine. By enabling PostgreSQL to handle certain updates without modifying index entries, HOT:

• reduces index bloat
• improves update speed
• enhances overall database performance
• minimizes vacuum pressure

For applications with high update volume, understanding and leveraging HOT updates can result in measurable, long-term gains.