Question: How can you scale out a PostgreSQL database?


Scaling out, also known as horizontal scaling, involves adding more nodes to a system to handle increased load, as opposed to scaling up (vertical scaling), which involves upgrading the existing hardware. For PostgreSQL, scaling out is crucial for applications that require high availability, load balancing, and handling large volumes of transactions or queries. Here are some common strategies for scaling out a PostgreSQL database:


Replication involves copying data from a primary database to one or more replicas. This helps distribute read queries across multiple nodes, improving read performance.

Streaming Replication: Streaming replication allows real-time copy of data from the primary server to replica servers.

-- On primary server, configure replication settings in postgresql.conf wal_level = replica max_wal_senders = 3 listen_addresses = '*' -- On replica server, connect to the primary server to start replication standby_mode = 'on' primary_conninfo = 'host=primary_host port=5432 user=rep_user password=rep_pass'


Partitioning breaks down a large table into smaller, more manageable pieces, while still allowing SQL queries to access the data as if it were a single table. This can be particularly useful for time-series data.

CREATE TABLE measurement ( city_id int not null, logdate date not null, peaktemp int, unitsales int ) PARTITION BY RANGE (logdate); CREATE TABLE measurement_y2020 PARTITION OF measurement FOR VALUES FROM ('2020-01-01') TO ('2021-01-01');


Sharding distributes data across multiple databases so that each database holds just a subset of the data. PostgreSQL does not natively support automatic sharding, but there are third-party tools like CitusDB that offer sharding capabilities on top of PostgreSQL.

Citus Example: Citus converts your PostgreSQL database into a distributed database, allowing you to shard your data across multiple nodes easily.

-- After installing Citus and creating a distributed table SELECT create_distributed_table('my_table', 'distribution_column');

Connection Pooling

Connection pooling manages a pool of database connections that can be reused by multiple clients, reducing the overhead of establishing connections, especially under heavy load.

PgBouncer is a popular, lightweight connection pooler for PostgreSQL.

# PgBouncer configuration file example [databases] mydb = host=localhost port=5432 dbname=mydb [pgbouncer] listen_port = 6432 listen_addr = auth_type = md5 auth_file = /etc/pgbouncer/userlist.txt

Use Cloud Services

Cloud services like Amazon RDS, Google Cloud SQL, and Azure Database for PostgreSQL provide managed PostgreSQL instances that can be easily scaled out through their interfaces, without needing extensive manual configuration.

In conclusion, scaling out a PostgreSQL database involves a combination of strategies tailored to the specific requirements of your application. Whether it's through replication, partitioning, sharding, connection pooling, or leveraging cloud services, these strategies can help manage larger datasets, increase throughput, and improve the overall performance of your applications.

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