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Case Studies: PostgreSQL, MongoDB, Cassandra

This generated surface maps a learner-facing curriculum unit to its canonical source routes.

Curriculum surface​

  • Open learner-facing unit
  • Curriculum path: content/curriculum/architecture/semester-06-databases-distributed/module-03-replication-partitioning/concepts/cluster-05-practical-systems/14-case-studies-postgresql-mongodb-cassandra-primary.md
  • App: architecture
  • Semester: semester-06-databases-distributed
  • Module: module-03-replication-partitioning
  • Unit kind: concept
  • Curation level: module_curated

Learning objectives​

  • Explain Case Studies: PostgreSQL, MongoDB, Cassandra in terms of topology, failure handling, and scaling tradeoffs instead of feature lists.
  • Use Case Studies: PostgreSQL, MongoDB, Cassandra to predict what breaks or changes when data is copied, partitioned, or rebalanced across nodes.
  • Use database-internals, ddia to connect the learner page to lag, routing, quorums, hotspots, and operational reality.

Prerequisites​

  • Comfort with storage-engine basics, indexing, and single-node database tradeoffs from the earlier modules.

Source books​

  • database-internals
  • ddia

Source routes​

Database Internals​

Ddia​

Supporting curriculum routes​

No supporting curriculum routes linked yet.

External enrichment​

  • PostgreSQL Documentation: Replication (official_docs_companion) - Useful when the learner needs an implementation-backed view of leader/follower replication and lag-related tradeoffs.
  • Jepsen Analyses (optional_deep_dive) - Provides concrete failure stories that sharpen the learner’s understanding of replication and partitioning tradeoffs.

AI companion modes​

  • Explain simply
  • Socratic tutor
  • Challenge my understanding
  • Diagnose my confusion
  • Connect forward / backward

Source-of-truth note​

This teaching unit is learner-facing guidance assembled from multiple canonical book routes. Use the listed source books as the primary conceptual spine for Case Studies: PostgreSQL, MongoDB, Cassandra, and treat outside material as supporting enrichment only.