Resources for further learning

For more in depth information about Indexing, Materialized views, Query optimization and Caching, the following resources could help.

Source	Vendor / Author	Summary
Indexing
PostgreSQL Documentation – Indexes	PostgreSQL Global Development Group	Official documentation covering B-tree, BRIN, GIN, GiST, and index variants (partial, covering).
MySQL Documentation - Indexes	MySQL / Oracle	Official documentation covering how to use Indexes in MySQL.
Use the Index, Luke!	Markus Winand	Practical online guide explaining indexing strategies, access paths, and query optimization in SQL databases.
Materialized Views
PostgreSQL Documentation – Materialized Views	PostgreSQL Global Development Group	Official documentation on creating, refreshing, and managing materialized views.
Oracle Database – CREATE MATERIALIZED VIEW	Oracle	Detailed reference for materialized views in Oracle, including refresh modes (complete, fast, on commit).
Partitioning
PostgreSQL Documentation – Table Partitioning	PostgreSQL Global Development Group	Official reference on partitioning methods (range, list, hash), setup, and optimizer behavior.
PostgreSQL Documentation – Schemas	PostgreSQL Global Development Group	Explains what schemas are, how they serve as namespaces in a database, how CREATE SCHEMA works, and how the search path and authorization work in PostgreSQL.
MVCC
PostgreSQL Documentation – Introduction to MVCC	PostgreSQL Global Development Group	Official introduction: what MVCC is, why PostgreSQL uses it, snapshot isolation, how reads/writes do not block each other.
DevCenter Heroku – PostgreSQL Concurrency with MVCC	Heroku	A more approachable tutorial explaining MVCC in Postgres, with practical examples of how it affects concurrency.
GeeksforGeeks – MVCC in PostgreSQL	GeeksforGeeks	Tutorial style explanation, covers snapshots, tuple versions, visibility rules.
Fast Serializable Multi-Version Concurrency Control for Main-Memory Database Systems	Neumann, Mühlbauer, Kemper	Academic paper: how to achieve serializable isolation with MVCC in main-memory DBs; good for students who want deeper theory.
Memory-Optimized Multi-Version Concurrency Control for Disk-Based Systems	Freitag, Kemper, Neumann	Evaluates a modern MVCC design optimized for memory/disk trade-offs; gives insight into the costs and design choices.
Caching
Database Caching Strategies Using Redis (AWS Whitepaper)	AWS / Redis	Explains cache-aside and write-through with pros/cons.
Redis – Caching Solutions	Redis	Defines cache-aside, write-through, and write-behind.
Azure Architecture Center – Cache-Aside Pattern	Microsoft Azure	Focuses on cache-aside (lazy loading) pattern.
Amazon ElastiCache – Caching Strategies	AWS / ElastiCache	Covers write-through and lazy loading strategies.
A Hitchhiker’s Guide to Caching Patterns	Hazelcast	Overview of cache-aside, read-through, and write-through.
Top 5 Caching Strategies Explained	Algomaster (blog)	Explicitly describes write-around strategy.
A Qualitative Study of Application-Level Caching — Mertz & Nunes	arXiv preprint, 2020	Empirical study of how developers implement and maintain cache-aside patterns in real-world projects.

💡 Note:
The terms cache-aside, write-through, write-back, and write-around are widely used in practice, but they are not formally standardized. Different vendors (AWS, Redis, Azure, Hazelcast) may use slightly different descriptions. Always specify what you mean in your own design or documentation.