Optimizing read and write operations is critical for scalable and flexible database systems. Two of the most effective strategies are the use of indexes and materialized views. Indexing is a fundamental technique that improves the speed of data retrieval operations on a table at the cost of additional writes and storage space. By creating indexes on columns that are frequently used in WHERE clauses, JOIN conditions, or as part of an ORDER BY, you can significantly reduce query execution times, especially as your data grows. For example, in the orders table, queries that filter by customer_id, order_date, or status will benefit from well-placed indexes.

-- Create an index on customer_id to speed up queries by customer
CREATE INDEX idx_orders_customer_id ON orders (customer_id);

-- Create an index on order_date to accelerate time-based queries
CREATE INDEX idx_orders_order_date ON orders (order_date);

-- Create a composite index for frequent status and date lookups
CREATE INDEX idx_orders_status_date ON orders (status, order_date);

While indexes are ideal for optimizing point lookups and narrow scans, complex analytical queries—such as aggregations and joins over large tables—can still be slow. This is where materialized views come into play. Unlike regular views, which compute their data on the fly every time they are queried, materialized views store the results of a query physically on disk. This means that expensive computations are performed only once and the results are reused, dramatically improving performance for recurring analytical queries. You can refresh a materialized view periodically or on demand to keep the data up to date. This pattern is especially useful for dashboards, reports, and summary tables that do not require real-time accuracy but need fast access to precomputed results.

-- Create a materialized view for sales summaries by product and month
CREATE MATERIALIZED VIEW sales_summary AS
SELECT
    p.name AS product_name,
    DATE_TRUNC('month', o.order_date) AS sales_month,
    SUM(o.quantity) AS total_quantity,
    SUM(o.quantity * p.price) AS total_sales
FROM
    orders o
JOIN
    products p ON o.product_id = p.product_id
GROUP BY
    p.name,
    DATE_TRUNC('month', o.order_date);