When it comes to database performance, query execution planning is one of the most critical factors. Every time a database receives a query, it must decide how to execute it in the most efficient way possible. This decision making process – known as query planning – can be expensive in terms of computation time, especially for frequently executed queries. To mitigate this overhead, databases employ Plan Caching, allowing them to reuse previously computed execution strategies instead of recalculating them for every execution.

However, the way plan caching works can differ significantly between database systems. PostgreSQL takes a more dynamic and adaptive approach to query plan caching, while SQL Server aggressively caches execution plans by default, leading to very different performance implications. For those familiar with SQL Server, transitioning to PostgreSQL can bring unexpected surprises, particularly in how queries are optimized over time.

This blog posting explores how PostgreSQL handles query plan caching, how it compares to SQL Server, and what you can do to optimize performance in each system. We will also discuss prepared statements, function caching, generic vs. custom plans, and common performance pitfalls in both databases.

How PostgreSQL Caches Query Plans

PostgreSQL does not automatically cache query plans for standard SQL statements. Each time a standard SQL query such as SELECT, INSERT, UPDATE, or DELETE is executed, PostgreSQL parses, optimizes, and executes the query from scratch.

This behavior is a big difference to SQL Server, which caches execution plans globally by default. While this might seem like a disadvantage at first, it actually allows PostgreSQL to make better optimization decisions in dynamic environments where data distribution changes over time. However, PostgreSQL does cache execution plans in certain scenarios, including prepared statements and PL/pgSQL functions. Let’s explore these in detail.

Prepared Statements and Query Plan Caching

To enable plan caching in PostgreSQL, you can use prepared statements. A prepared statement allows PostgreSQL to cache the execution plan of a query so that it does not need to recompile it each time it is executed.

PREPARE get_users (INT) AS
SELECT * FROM users WHERE age > $1;

EXECUTE get_users(30);

In this example:

• The first time PREPARE is called, PostgreSQL parses and plans the query.
• When EXECUTE is run, the cached plan is reused, avoiding additional parsing and planning overhead.

Custom Plans vs. Generic Plans

By default, PostgreSQL starts with a custom plan – one that is optimized for the specific parameter values used. However, if a prepared statement is executed multiple times (typically 5 or more times), PostgreSQL evaluates whether it should switch to a generic plan instead. A custom plan is optimized based on actual parameter values and may use an index scan, sequential scan, or other optimized execution path depending on data distribution.

A generic plan, on the other hand, is computed without specific parameter values and instead relies on table statistics from pg_statistic to estimate row selectivity. This approach eliminates per-execution planning overhead but may lead to suboptimal query execution if data distribution is skewed.

PL/pgSQL Functions and Execution Plan Caching

PostgreSQL also caches execution plans inside PL/pgSQL functions. When a function contains SQL statements, PostgreSQL caches the execution plan after the first execution.

CREATE FUNCTION get_users_by_age(age_limit INT)
RETURNS SETOF users AS $$
BEGIN
    RETURN QUERY SELECT * FROM users WHERE age > age_limit;
END;
$$ LANGUAGE plpgsql;

The first time this function runs, PostgreSQL creates a cached plan for the SELECT statement. If the function is called frequently, PostgreSQL may switch to a generic plan, just like with prepared statements. To control this behavior, PostgreSQL allows developers to manually force a specific caching strategy:

ALTER FUNCTION get_users_by_age SET plan_cache_mode = 'force_custom_plan';
ALTER FUNCTION get_users_by_age SET plan_cache_mode = 'force_generic_plan';

Understanding Execution Plan Behavior with Indexes

A major factor in PostgreSQL’s decision to use a custom or generic plan is index selectivity. If a column has high cardinality (many unique values), an index scan is usually the best choice. However, if a column has low cardinality (few unique values), a sequential scan might be more efficient. For example, consider the following:

CREATE INDEX idx_users_age ON users(age);

If most age values are evenly distributed, PostgreSQL may prefer a generic plan because parameter variation doesn’t significantly affect execution time. However, if some values occur frequently (for example: age = 25 accounts for 60% of rows), using a custom plan will be more effective.

Summary

Understanding how query plan caching works is crucial for database performance tuning. PostgreSQL takes a dynamic approach, avoiding the pitfalls of parameter sniffing but requiring explicit configuration for plan reuse. SQL Server, on the other hand, aggressively caches execution plans, which can reduce planning overhead but introduce issues when parameter values vary widely. You can find more information about how to deal with Parameter Sniffing problems in SQL Server in this and this blog posting.

For those transitioning from SQL Server to PostgreSQL, adapting to PostgreSQL’s caching behavior can take time. However, with careful use of prepared statements, functions, and plan_cache_mode settings, developers can fine-tune PostgreSQL for optimal performance while avoiding SQL Server’s common pitfalls.

Thanks for your time,

-Klaus