PostgreSQL, MongoDB, or Cassandra: How Multi-Node Architecture Changes Everything

Single-node performance differences between databases become largely irrelevant once a second node is added, as network latency — measured in milliseconds — dwarfs storage-engine optimizations measured in microseconds. Network partitions introduce a new failure class unique to distributed systems, forcing each database to make architectural trade-offs that reveal its core design philosophy. PostgreSQL was originally built as a single-node database, meaning all its distributed capabilities — replication, connection pooling, and sharding — were added later as external tooling. Running PostgreSQL at scale requires additional components like Patroni for high availability, PgBouncer for connection pooling, and Citus for horizontal scaling. A key configuration decision in PostgreSQL clusters is whether to use synchronous or asynchronous replication, with the default asynchronous mode offering faster commits but risking data loss if the primary node crashes before replication completes.