Indexes are like shortcuts for your database. They help you find rows faster by pointing to where the data is. Make sure to create indexes on columns you often search, like primary keys or columns in WHERE, JOIN, and ORDER BY clauses.

CREATE INDEX index_name ON table_name (column_name);

Instead of grabbing all rows at once, use LIMIT and OFFSET to paginate your queries. This way, you reduce the data load and speed up responses.

SELECT * FROM table_name ORDER BY column_name LIMIT 10 OFFSET 20;

Avoid using SELECT *. Just ask for the columns you need. This cuts down on data transfer and boosts performance.

SELECT column1, column2 FROM table_name WHERE condition;

The EXPLAIN statement is your friend. It shows how PostgreSQL executes your queries, helping you spot bottlenecks and optimize them.

EXPLAIN SELECT * FROM table_name WHERE condition;

Materialized views store query results physically and can be refreshed periodically. They speed up complex queries by providing precomputed results.

CREATE MATERIALIZED VIEW view_name AS SELECT * FROM table_name WHERE condition;
REFRESH MATERIALIZED VIEW view_name;

Regularly vacuum and analyze your database. Vacuuming cleans up dead tuples, and analyzing updates the planner's statistics.

VACUUM ANALYZE;

Connection pooling reuses existing connections, reducing the overhead of establishing new ones. Enable Supabase's built-in connection pooling for better performance under heavy load.

# Assuming Supabase configuration, see Supabase docs for enabling connection pooling

Make sure joined columns are indexed and use the right join strategies (like INNER JOIN, LEFT JOIN) to minimize data processing during joins.

SELECT a.*, b.* 
FROM table_a a 
JOIN table_b b 
ON a.common_column = b.common_column;

Think about caching frequently accessed data at the application level using a solution like Redis. This cuts down on the number of database queries.

# Example Redis caching configuration

Partitioning large tables can make queries faster by breaking the table into smaller, more manageable pieces based on a specified column.

CREATE TABLE parent_table (id SERIAL, data TEXT, created_at TIMESTAMP) 
PARTITION BY RANGE (created_at);

CREATE TABLE partition_table_2023 PARTITION OF parent_table 
FOR VALUES FROM ('2023-01-01') TO ('2024-01-01');

Use monitoring tools to keep an eye on database performance and spot any slow queries or bottlenecks. Supabase offers monitoring capabilities right in its dashboard.

# Example of monitoring via Supabase dashboard

Implementing these steps helps in optimizing queries in Supabase for better performance.