PG18 Hacktober:31 Days of New Features Temporal Constraints

Welcome to the 15th blog post of PG18 Hacktober!

PostgreSQL 18 introduces powerful temporal constraints that help manage and validate time-based data directly within the database schema. These constraints ensure that time periods, such as validity ranges or historical records, do not overlap or conflict with each other. This enhancement makes it easier to maintain accurate historical information and enforce data integrity rules over time without relying on complex triggers or manual checks.

What are Temporal constraints?

Temporal constraints are schema-level rules that control how range/time-related data behaves, most commonly by preventing overlapping time ranges for the same entity. Following are some of the use cases we’ve been working with our customers:

• Employee assignments
• Historical prices
• Validity periods
• Contracts, sessions, or events

Before PostgreSQL 18, enforcing this logic required manual checks or triggers. Now, you can define it declaratively using exclusion constraints with time range types

Primary Key with Temporal Constraint

You can combine a primary key with a temporal exclusion constraint to prevent overlapping periods while still uniquely identifying rows.

CREATE EXTENSION IF NOT EXISTS btree_gist;

CREATE TABLE employee_salary (
    emp_id INT NOT NULL,
    valid_period TSRANGE NOT NULL,
    salary NUMERIC NOT NULL,
    
    PRIMARY KEY (emp_id, valid_period),
    
    -- Prevent overlapping periods for the same employee
    EXCLUDE USING gist (
        emp_id WITH =,
        valid_period WITH &&
    )
);

Explanation:

• PRIMARY KEY (emp_id, valid_period) ensures each (emp_id, valid_period) pair is unique.
• EXCLUDE USING gist ensures no overlapping periods for the same employee.

Test Case

— Works

INSERT INTO employee_salary VALUES (1, '[2025-01-01,2025-03-01)', 5000);

— Fails (overlaps previous period)

INSERT INTO employee_salary VALUES (1, '[2025-02-15,2025-04-01)', 5200);

Result:

postgres=#
postgres=# INSERT INTO employee_salary VALUES (1, '[2025-02-15,2025-04-01)', 5200);
ERROR:  conflicting key value violates exclusion constraint "employee_salary_emp_id_valid_period_excl"DETAIL:  Key (emp_id, valid_period)=(1, ["2025-02-15 00:00:00","2025-04-01 00:00:00")) conflicts with existing key (emp_id, valid_period)=(1, ["2025-01-01 00:00:00","2025-03-01 00:00:00")).
postgres=#

Foreign Key with Temporal Constraint

You can enforce referential integrity while also validating time periods.

CREATE TABLE employee (
    emp_id INT PRIMARY KEY,
    name TEXT NOT NULL
);

CREATE TABLE employee_assignment (
    assignment_id SERIAL PRIMARY KEY,
    emp_id INT NOT NULL,
    project_id INT NOT NULL,
    assignment_period DATERANGE NOT NULL,

    -- Foreign key reference to employee
    CONSTRAINT fk_employee FOREIGN KEY (emp_id) REFERENCES employee(emp_id),

    -- Temporal constraint to avoid overlapping assignments for the same employee
    EXCLUDE USING gist (
        emp_id WITH =,
        assignment_period WITH &&
    )
);
INSERT INTO employee (emp_id, name) VALUES (1, 'Alice');

Test Case

— Works: emp_id exists and no overlap

INSERT INTO employee_assignment (emp_id, project_id, assignment_period)
VALUES (1, 101, '[2025-01-01,2025-03-01)');

— Fails: overlapping period

INSERT INTO employee_assignment (emp_id, project_id, assignment_period)
VALUES (1, 102, '[2025-02-15,2025-04-01)');

— Fails: emp_id does not exist

INSERT INTO employee_assignment (emp_id, project_id, assignment_period)
VALUES (99, 103, '[2025-03-01,2025-06-01)');

Unique Constraint with Temporal Constraint

You can combine unique constraints on columns along with temporal constraints.

CREATE TABLE product_price (
    product_id INT NOT NULL,
    region TEXT NOT NULL,
    price NUMERIC NOT NULL,
    valid_period TSRANGE NOT NULL,

    -- Unique combination of product and region per period
    UNIQUE (product_id, region, valid_period),
    
    -- Prevent overlapping periods for the same product in the same region
    EXCLUDE USING gist (
        product_id WITH =,
        region WITH =,
        valid_period WITH &&
    )
);

Test Case

— Works

INSERT INTO product_price VALUES (1, 'US', 100, '[2025-01-01,2025-03-01)');

— Fails: overlapping period for the same product and region

INSERT INTO product_price VALUES (1, 'US', 120, '[2025-02-15,2025-04-01)');

— Works: same period but different region

INSERT INTO product_price VALUES (1, 'EU', 110, '[2025-01-01,2025-03-01)');

Key Differences

Feature / Behavior	Before PostgreSQL 18	Functionality in PostgreSQL 18
Temporal integrity	No built-in support; had to use triggers, application logic, or manual checks	Built-in support using temporal constraints
Overlap prevention	Checked manually via queries or triggers	Automatic prevention using exclusion constraints (EXCLUDE USING gist)
Range types	Could store ranges (daterange, tsrange) but enforcement was manual	Works seamlessly with DATERANGE, TSRANGE, TSTZRANGE
Ease of use	Complex, error-prone, and hard to maintain	Declarative, concise, and reliable at the schema level
Concurrency safety	Tricky; race conditions possible	Fully handled by PostgreSQL’s constraint enforcement

Best Practices

• Use btree_gist when combining multiple data types in an exclusion constraint
• Clearly document range boundaries ([ inclusive, ) exclusive)
• Test for edge cases (back-to-back ranges, partial overlaps)
• Indexing: Exclusion constraints auto-create GiST indexes, but add others for frequent queries

Advantages of Temporal Constraints

• Automatic conflict prevention for overlapping periods
• Works seamlessly with primary/foreign/unique keys
• Reduces complexity by removing the need for triggers
• Supports all temporal use cases — from time zones to simple date ranges
• Scalable: concurrency-safe and enforced by the engine

Conclusion

Temporal constraints in PostgreSQL 18 are a powerful tool for managing time-sensitive data. By combining range types (DATERANGE, TSRANGE, TSTZRANGE) with exclusion constraints, you can:

• Prevent overlapping validity periods
• Model historical and versioned data with ease
• Maintain integrity without triggers or extra logic
• Combine with relational constraints for full schema enforcement

Whether you’re building systems for HR, pricing, scheduling, or historical tracking, this feature will simplify your architecture and strengthen your data integrity. This makes PostgreSQL 18 especially suitable for enterprise applications that need robust historical tracking or time-based validations.