Scale PostgreSQL Horizontally with Sharding Techniques

PostgreSQL Sharding: Scaling Your Database Horizontally

Sharding is a database scaling technique that distributes data across multiple servers. PostgreSQL supports sharding through extensions like Citus and manual partitioning, enabling horizontal scalability for applications with large datasets.

1. What is Sharding?

Sharding divides large datasets into smaller, manageable pieces (shards) stored across multiple nodes. Each shard contains a subset of data based on defined criteria, like a range or hash.

2. When to Use Sharding?

• Large datasets exceeding a single node’s capacity.
• Applications with high query traffic.
• Need for high availability and reduced latency.

3. PostgreSQL Sharding Approaches

A. Manual Sharding

Split tables into multiple smaller tables manually, distribute them across nodes, and manage connections in the application logic.

B. Citus Extension

Citus transforms PostgreSQL into a distributed database by automatically sharding data across nodes.

4. Setting Up Sharding with Citus

Install Citus:

sudo apt install postgresql-15-citus   

Enable Citus Extension:

CREATE EXTENSION citus;      

Distribute a Table:

SELECT create_distributed_table('my_table', 'distribution_column');  

5. Example Sharding Query with Citus

Assume you have a table orders with order_id as the distribution column:

SELECT create_distributed_table('orders', 'order_id');  
INSERT INTO orders (order_id, customer_id, amount) VALUES (1, 1001, 250.00);  

6. Advantages of Sharding in PostgreSQL

7. Challenges of Sharding

• Increased complexity in query execution.
• Potential cross-shard latency for joins.
• Requires careful schema design and data distribution.

8. Sharding Best Practices

• Choose a distribution column wisely (e.g., primary key or frequently filtered column).
• Monitor node performance and rebalance shards periodically.
• Use a connection pooler like PgBouncer for managing shard connections.

Use Case Example

Large E-Commerce Platform

For platforms handling millions of transactions daily, sharding enables scalability by splitting orders and customers tables across multiple nodes.

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