Explain Redis In-Memory Data Structures and Common Caching Patterns (Cache-Aside, Write-Through, Write-Behind).

Redis is an open-source, in-memory key-value data structure store utilized as a database, cache, message broker, and streaming engine.

Core Data Structures:

• Strings: Binary-safe strings, integers, atomic counters (INCR, DECR).
• Hashes: Field-value pairs representing structured objects (e.g. user session tokens).
• Lists: Linked lists supporting FIFO queues or LIFO stacks (LPUSH, RPOP).
• Sets & Sorted Sets (ZSet): Unique unordered collections, and scored ordered sets ideal for leaderboards and rate limiting.

Caching Patterns:

• Cache-Aside (Lazy Loading): Application checks cache; on miss, reads from DB and populates cache. High resilience against cache downtime.
• Write-Through: Application writes to cache first; cache immediately updates database synchronously. Strong consistency.
• Write-Behind (Write-Back): Application writes to cache, which asynchronously flushes updates to database in batches. High write throughput, risk of data loss on node crash.