36. Database & Storage in System Design | Block, File, Object Storage & Tradeoffs
In this video, we take a deep, engineering-level dive into Database and Storage design in system design, focusing on real-world production tradeoffs that SDE-2 and SDE-3 engineers face every day.
This lecture goes beyond surface-level explanations and covers how storage systems actually behave under scale, latency, failures, and growth.
Topics covered in this video:
Block Storage vs File Storage vs Object Storage explained with architecture
When and why databases rely on block storage
Why object storage became the default choice for modern systems
Common production issues: IOPS throttling, snapshot impact, network latency
Redis and in-memory storage beyond caching
Cache-aside, write-through, and write-behind patterns
Redis use cases: leaderboards, rate limiting, distributed locks
Durability levels from single machine to geo-replication
Availability math and redundancy myths
Active-passive vs active-active architectures
Consistency models: strong, eventual, and causal consistency
CAP theorem explained with real system examples
Latency budgets and database performance bottlenecks
Vertical vs horizontal scaling strategies
Sharding techniques and cross-shard query challenges
Who should watch this:
SDE-2 and SDE-3 engineers
Backend and full-stack developers
Engineers preparing for system design interviews
Anyone designing high-scale distributed systems
Developers moving from theory to real production systems
By the end of this video, you’ll have clear mental models to design storage systems that are scalable, reliable, and cost-efficient.
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