7. Mismanaging sharding and partitioning

Proprietary database vendors often promote the idea that only their solutions can handle enterprise-scale workloads, sometimes implying that open source databases lack sophisticated partitioning and sharding capabilities. In reality, PostgreSQL offers powerful scaling features, including declarative partitioning built into the core system and well-integrated ecosystem solutions like Citus Data for horizontal scaling (sharding).

When a PostgreSQL database grows beyond a certain size, effective partitioning and/or sharding become essential for performance and manageability. Success, however, depends on adopting PostgreSQL-native methods rather than trying to force-fit paradigms from other database systems, due to differences in architecture (like MVCC) and query planning. This involves:

• Using declarative partitioning to optimize query performance and simplify management compared to older manual methods.
• Leveraging extensions like Citus for distributed workloads that require horizontal scaling across multiple nodes.
• Balancing read and write traffic strategically across partitions or shards to prevent bottlenecks.
• Regularly evaluating query plans and indexing strategies to ensure partitioned or sharded data performs efficiently.

Consider this: While proprietary vendors often highlight unique or patented technologies for scaling, PostgreSQL's native partitioning and available distributed architectures (like those using Citus) demonstrably handle demanding enterprise workloads and can achieve performance levels comparable, and in many cases favorable, relative to proprietary alternatives, particularly when considering total cost of ownership. Scaling any large database system involves complexity, but organizations find that PostgreSQL provides the necessary tools and flexibility to scale effectively, often without the licensing constraints sometimes associated with proprietary solutions.