Observed Signal · Jul 2, 2026 · Explainer · Source: DEV Community · Impact: 2/5 · Sentiment: Neutral
PostgreSQL vs MongoDB vs Cassandra: Multi‑Node Differences
This technical explainer compares PostgreSQL, MongoDB, and Cassandra in multi-node deployments, focusing on replication, scaling, consistency, and transactional behavior. PostgreSQL is a single-node-first system with streaming WAL replication, synchronous/asynchronous trade-offs, and CP behavior; horizontal write scaling requires external tooling or extensions like Citus and incurs two‑phase commit costs for cross-shard transactions. MongoDB provides native replica sets and a logical oplog, configurable per-operation consistency via writeConcern/readPreference, and a built-in sharding architecture (mongos, config servers, shard replica sets) but advises avoiding cross-shard transactions where possible. Cassandra was designed for distribution from day one, using a consistent-hashing ring with vnodes, leaderless replication, tunable per-query consistency (ONE/QUORUM/ALL), hinted handoff, and limits on multi-partition transactions (LWT for single-partition conditional writes). The author concludes with a decision framework and recommends PostgreSQL as the honest default for new products unless specific scale or availability needs dictate otherwise.
Practical, technical guidance on multi-node database selection and trade-offs relevant to infrastructure architects and engineers; useful but not industry‑shifting.
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Key Takeaways & Evidence Grounding
- PostgreSQL was designed as a single-node database; its multi-node features (streaming replication, logical replication, connection pooling, sharding) were added on top and often require external tooling such as Patroni, repmgr, PgBouncer, or Citus.
- PostgreSQL uses WAL streaming for replication; asynchronous mode acknowledges commits locally and risks recent-commit loss, while synchronous mode waits for standby acknowledgment and adds network latency (typical intra-datacenter 1–3ms; cross-datacenter 50–100ms).
- MongoDB implements native replica sets with a logical oplog; write durability is controlled per operation via writeConcern (e.g., w:1 vs w:majority), and sharded clusters use mongos routers, config servers, and shard replica sets with shard-key-driven data distribution.
- Cassandra was built for distribution: it uses a consistent-hashing ring with token ranges and vnodes, supports leaderless replication where any node can coordinate writes, and exposes tunable consistency levels (ONE, QUORUM, ALL) plus hinted handoff and LWT (Paxos) for single-partition conditional writes.
- Cross-node transactions: PostgreSQL provides full ACID on a single primary and uses 2PC in sharded setups; MongoDB supports multi-document ACID transactions (2PC across shards) but recommends data modeling to avoid cross-shard transactions; Cassandra has no multi-partition transactions and relies on application-side patterns.
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1 Entity mapped“MongoDB designed replication as a native feature from early in its history, and it shows....”
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ClickHouse vs PostgreSQL: OLAP vs OLTP Comparison
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