Relational database strengths in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Why are relational databases strong in data integrity?

Relational databases use certain features to ensure data stays accurate and consistent. Which feature best explains this strength?

A They use key-value pairs without relationships.

B They store data in flat files for easy access.

C They allow unlimited schema changes without restrictions.

D They use transactions with ACID properties to keep data consistent.

💡 Hint

Think about how databases keep data reliable during multiple operations.

Relational databases use ACID transactions to ensure that all operations complete fully or not at all, preserving data integrity.

❓ Architecture

intermediate

Which relational database feature supports complex queries?

Relational databases allow users to retrieve data using powerful queries. Which feature enables this?

A No support for indexing.

B Structured Query Language (SQL) with JOIN operations.

C Using simple key-value lookups only.

D Storing data as JSON documents.

💡 Hint

Think about how you combine data from multiple tables.

SQL supports JOINs that combine rows from two or more tables based on related columns, enabling complex queries.

❓ scaling

advanced

What is a common challenge when scaling relational databases horizontally?

Relational databases are strong but face challenges when scaling out. What is a typical issue?

A Maintaining data consistency across distributed nodes.

B Lack of support for structured data.

C Inability to perform transactions.

D No support for indexing.

💡 Hint

Think about what happens when data is spread across many servers.

When scaling horizontally, relational databases must keep data consistent across nodes, which is complex and can impact performance.

❓ tradeoff

advanced

What tradeoff do relational databases make to ensure strong consistency?

Relational databases prioritize strong consistency. What is a common tradeoff they make?

A Unlimited schema flexibility.

B No support for transactions.

C Reduced availability during network partitions.

D No data validation.

💡 Hint

Consider the CAP theorem and what happens when network issues occur.

To maintain strong consistency, relational databases may sacrifice availability during network partitions, following the CAP theorem.

❓ estimation

expert

Estimate the maximum number of concurrent transactions a relational database can handle given these specs

A relational database server has 16 CPU cores and 64 GB RAM. Each transaction requires 50 MB RAM and 1 CPU core for processing. What is the maximum number of concurrent transactions it can handle without swapping or CPU contention?

A 16 transactions

B 64 transactions

C 128 transactions

D 32 transactions

💡 Hint

Calculate limits based on CPU cores and RAM separately, then choose the smaller number.

CPU limits concurrency to 16 (cores). RAM allows 64 GB (65536 MB) / 50 MB ≈ 1310 transactions. The bottleneck is CPU, so max concurrency is 16.