PostgreSQL provides a wealth of tools that database professionals can use to fine-tune performance, handle large datasets efficiently, and manage intermediate data smartly. Among these tools, Temporary Tables, UNLOGGED Tables, and Materialized Views stand out as solutions designed to manage different types of data lifecycles.
Although they seem similar at a glance, each storing some kind of intermediate or derived data, they behave quite differently under the hood. This blog explores when and how to use each of them, along with the internal PostgreSQL mechanics and relevant system catalogs involved.
Temporary Tables
What They Are
Temporary tables in PostgreSQL are session-scoped objects used to hold transient data. They are automatically dropped at the end of a session or optionally at the end of a transaction.
Syntax
CREATE TEMP TABLE temp_sales (
id SERIAL,
customer_name TEXT,
amount NUMERIC
);
You can also use LOCAL TEMPORARY or simply TEMP.
How They Work Internally
When a temporary table is created, PostgreSQL places it in a session-specific schema named pg_temp_. This schema is isolated from other sessions. Each user can safely create a temporary table with the same name without conflict.
Temporary tables do not generate WAL (Write-Ahead Logging). This means changes to them are not logged in the WAL, which leads to faster performance but with a major trade-off: they are not crash-safe.
Additionally, temporary tables are held in memory where possible, with disk spillover when data grows large.
Behavior on Server Restart
Temporary tables are automatically removed on session termination, including when the database server restarts. Because they’re never persisted to disk with WAL, PostgreSQL doesn’t attempt to recover them after a crash or restart. They are completely ephemeral.
Relevant pg_catalog Views
- pg_class – Temporary tables appear here during the session
- pg_namespace – You'll see temporary schemas like pg_temp_3
- pg_attribute – Lists the columns of the temporary table during the session lifespan
UNLOGGED Tables
What They Are
UNLOGGED tables are similar to regular tables but skip the WAL system entirely. They provide better performance for write-heavy operations by avoiding disk I/O related to WAL logging.
Syntax
CREATE UNLOGGED TABLE staging_events (
id SERIAL,
payload JSONB,
created_at TIMESTAMP
);
How They Work Internally
UNLOGGED tables are part of the system catalogs, just like permanent tables, and exist across sessions. The critical difference is that they bypass the WAL system entirely, which makes inserts, updates, and deletes faster than in regular tables.
However, this comes with a significant caveat: UNLOGGED tables lose all their data if the PostgreSQL server crashes or is restarted unexpectedly. Upon restart, PostgreSQL automatically truncates all UNLOGGED tables, not the schema or table definition, but all data inside.
UNLOGGED tables can have indexes and constraints like regular tables. But they cannot be used with logical replication, and their data is not durable across crashes.
Behavior on Server Restart
When PostgreSQL starts up, it truncates UNLOGGED tables. This is handled by writing a small flag file when such a table is modified. If PostgreSQL crashes before that table is synced, the table is emptied on recovery.
This mechanism ensures consistency but confirms the non-durability of the data.
Relevant pg_catalog Views
- pg_class.relpersistence = 'u' – Another indicator of unlogged persistence
- pg_stat_user_tables – Tracks I/O and stats even for UNLOGGED tables
Materialized Views
What They Are
Materialized views are database objects that store the result of a query physically on disk. They are especially useful for caching expensive queries or periodic reporting.
Syntax
CREATE MATERIALIZED VIEW monthly_revenue AS
SELECT department, SUM(amount) AS total
FROM invoices
WHERE invoice_date >= date_trunc('month', CURRENT_DATE)
GROUP BY department;
To refresh the view:
REFRESH MATERIALIZED VIEW monthly_revenue;
How They Work Internally
Materialized views generate and store actual tuples, much like a table, and are WAL-logged. This ensures full crash recovery and participation in backup/restore mechanisms.
Unlike regular views, which run the query every time they are accessed, materialized views store results and serve them as static data. You must manually refresh them to reflect underlying data changes.
Internally, PostgreSQL creates a hidden table under the hood and stores the output of the query in that table. When you REFRESH, PostgreSQL truncates and refills this backing table.
Behavior on Server Restart
Materialized views are persistent and crash-safe. Because their data is WAL-logged, PostgreSQL ensures their integrity through checkpoints and crash recovery.
Relevant pg_catalog Views
- pg_class.relkind = 'm' – Identifies materialized views
- pg_matviews – Provides view definition and other metadata
- pg_rewrite and pg_depend – Show query tree and dependency links to source tables
When to Use What
Use Temporary Tables when:
- You need data only during a session or transaction
- You want fast inserts/updates and don’t need crash safety
- The data is intermediate and doesn’t need persistence
Use UNLOGGED Tables when:
- Performance is critical and data can be regenerated
- You’re importing/staging a large volume of data
- You’re building caches or temporary analytic datasets
Use Materialized Views when:
- You have long-running queries and can tolerate stale data
- You want pre-aggregated data for dashboards or reports
- You’re optimizing query performance in analytical workloads
Conclusion
Understanding the internal behavior and design of PostgreSQL's storage options is critical to using them effectively. While temporary tables offer fast, session-bound storage, UNLOGGED tables bring high-speed, cross-session persistence at the cost of crash durability. Materialized views, on the other hand, bring the power of precomputed data, perfect for speeding up heavy reporting queries.
Each option is best suited for a specific use case. As a database administrator or developer, your goal should be to evaluate the nature of your data, its lifespan, durability needs, and performance constraints, and choose accordingly.
PostgreSQL empowers users with these powerful mechanisms to fine-tune data architecture. Understanding how they interact with internal components like WAL, the system catalogs (pg_class, pg_namespace, pg_matviews, etc.), and crash recovery systems can lead to more robust, high-performance designs.
If you're looking to optimize workloads, simplify complex pipelines, or reduce query times, then knowing when to use temporary tables, UNLOGGED tables, or materialized views is a vital step toward efficient PostgreSQL development.