In the third episode of my“Understanding the System” series, we dive into one of the most essential building blocks of modern software systems:Databases.

Whether you're building a startup product, scaling a SaaS platform, or trying to optimize performance, how you handle data will either set you up for long-term success — or become a bottleneck. In this video, I break down thecore concepts,failure points, andscaling strategies you need to understand to make smart database decisions.

🧱 Relational vs Non-Relational Databases

We start by understanding the two main types of databases:

• Relational (SQL): Uses structured tables and schemas. Best for consistent, transactional data like financial systems and user accounts. Think PostgreSQL or MySQL.
• Non-Relational (NoSQL): Flexible, schema-less data. Ideal for large-scale, fast-changing data like logs or analytics. Think MongoDB, Redis, or Cassandra.

💡 When to pick which? If you need strong consistency and well-structured data, go SQL. If you need speed and flexibility, NoSQL may be better.

⚙️ Core Concepts Every Engineer Should Know

• ACID Transactions: These guarantee reliable data operations.
• Normalization: Reduces redundancy in SQL databases.
• ORMs (Object Relational Mappers): Helpful but may introduce performance issues (like the N+1 problem).
• Caching: Improve performance by reducing direct DB hits (using Redis or Memcached).
• Profiling Queries: Know where your bottlenecks are before scaling.

📈 Scaling Databases

As traffic grows, databases can become a bottleneck. The video explains:

• Indexes: To speed up reads.
• Replication: For high availability.
• Sharding: Splitting data across machines.
• CAP Theorem: The trade-off between consistency, availability, and partition tolerance.

🧪 Failure Modes and Migrations

I also touch on what can go wrong — from deadlocks to query spikes — and how to handle schema migrations safely using tools and versioning.

🎥 Watch the Full Breakdown

This blog is just a surface-level summary. The video goes into visuals, examples, and detailed explanations that help youunderstand databases from a system design perspective.

👉Watch on YouTube(https://www.youtube.com/watch?v=tq68X1fv7vM)
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