PostgreSQL does not have a dedicated Row Store Index as a specific index type because it fundamentally follows a row-oriented storage model where data is stored row by row in tables. However, PostgreSQL supports a variety of index types and features that can achieve similar goals depending on the use case.

Understanding Row Store Index

• A Row Store Index is typically associated with databases that use columnar storage, where a separate index or mechanism exists to facilitate fast retrieval of rows across columns.
• In PostgreSQL, the default storage format is row-oriented, and therefore, data retrieval is already row-based. Index types in PostgreSQL optimize access to specific rows based on column values, eliminating the explicit need for a row store index.

Index Types in PostgreSQL Relevant to Row Store Needs

PostgreSQL provides multiple index types that support efficient row retrieval based on conditions:

1. B-Tree Index (Default)

• B-Tree is the most commonly used index type, and it supports equality and range queries efficiently.
• Use Case: Retrieve rows based on ordered or unique values in columns.
• Example:

CREATE INDEX idx_orders_customer_id ON orders (customer_id);
SELECT * FROM orders WHERE customer_id = 12345;

2. GIN (Generalized Inverted Index)

• Designed for indexing composite data types like arrays, JSONB, or full-text search.
• Use Case: Efficient retrieval of rows with array or document-based data structures.
• Example:

CREATE INDEX idx_orders_meta ON orders USING GIN (meta);
SELECT * FROM orders WHERE meta @> '{"key": "value"}';

3. BRIN (Block Range Index)

• Stores metadata for ranges of table blocks, optimized for sequential access to rows.
• Use Case: Works well for large tables where data is inserted sequentially, such as logs or time-series data.
• Example:

CREATE INDEX idx_transactions_date ON transactions USING BRIN (transaction_date);
SELECT * FROM transactions WHERE transaction_date BETWEEN '2023-01-01' AND '2023-01-31';

4. Covering Index (INCLUDE Clause)

• Extends a B-Tree index to include additional columns that are not part of the index key but can be fetched directly.
• Use Case: Avoids fetching rows from the heap for queries using indexed columns and included columns.
• Example:

CREATE INDEX idx_orders_customer_id_incl ON orders (customer_id) INCLUDE (status, created_at);
SELECT status, created_at FROM orders WHERE customer_id = 12345;

PostgreSQL Features That Simulate Row Store Index Behavior

1. Index-Only Scans

• PostgreSQL supports Index-Only Scans, where the index itself contains all the data needed for a query, eliminating the need to access the main table (heap).
• How it Helps: Works like a "row store index" by fetching data efficiently if all required columns are in the index.
• Example:

CREATE INDEX idx_orders_customer_id_status ON orders (customer_id, status);
SELECT customer_id, status FROM orders WHERE customer_id = 12345;

2. Materialized Views

• Materialized views can act as a precomputed row store, providing optimized access to commonly queried row combinations.
• How it Helps: For repetitive complex queries, the materialized view serves as a "snapshot" of rows.
• Example:

CREATE MATERIALIZED VIEW mv_orders_summary AS
SELECT customer_id, COUNT(*) AS total_orders
FROM orders
GROUP BY customer_id;

3. Partitioning

• Declarative partitioning allows dividing a table into smaller, row-oriented storage units based on column values.
• How it Helps: Limits the rows scanned by queries to specific partitions, mimicking row store indexing behavior.
• Example:

CREATE TABLE transactions (
    transaction_id SERIAL,
    transaction_date DATE,
    amount NUMERIC
) PARTITION BY RANGE (transaction_date);

When to Use Alternatives

If you're looking for advanced row-based optimizations that mimic a row store index, consider using:

• TimescaleDB (PostgreSQL Extension): Provides native support for time-series data and row-oriented optimizations.
• Columnar Storage: Use extensions like cstore_fdw for columnar data storage if the workload involves analytical queries.

Conclusion

PostgreSQL does not explicitly have a Row Store Index because its default row-oriented storage and various index types (e.g., B-Tree, BRIN, GIN) already optimize row-based access. Features like index-only scans, covering indexes, and partitioning provide functionality equivalent to row store indexing in most use cases.

Implementing the Materialized Path Model in PostgreSQL: A Step-by-Step Guide

How Materialised Views work in PostgreSQL?

PostgreSQL Indexes