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.

Practice

1. Which of the following is a key strength of relational databases?

easy

A. They are best suited for storing large binary files.

B. They ensure strong data consistency across multiple users.

C. They store data in unstructured formats like documents.

D. They do not support complex queries.

Solution

1. Step 1: Understand relational database data organization

   Relational databases organize data in tables with relationships, which helps maintain consistency.

2. Step 2: Identify the strength related to multi-user access

   They support multiple users accessing and modifying data while keeping it accurate and consistent.

3. Final Answer:

   They ensure strong data consistency across multiple users. -> Option B

4. Quick Check:

   Data consistency = C [OK]

Hint: Relational = tables + strong consistency [OK]

Common Mistakes:

• Confusing relational with document databases
• Thinking relational databases store unstructured data
• Assuming relational databases don't support complex queries

2. Which SQL keyword is used to combine rows from two tables based on a related column?

easy

A. UPDATE

B. SELECT

C. INSERT

D. JOIN

Solution

1. Step 1: Recall SQL keywords for combining tables

   The JOIN keyword is used to combine rows from two or more tables based on a related column.

2. Step 2: Differentiate from other SQL commands

   SELECT retrieves data, INSERT adds data, UPDATE modifies data, but JOIN combines tables.

3. Final Answer:

   JOIN -> Option D

4. Quick Check:

   Combine tables = JOIN [OK]

Hint: JOIN combines tables on related columns [OK]

Common Mistakes:

• Confusing SELECT with JOIN
• Using INSERT or UPDATE to combine tables
• Not knowing JOIN syntax

3. Given two tables Users and Orders, what will the following SQL query return?

SELECT Users.name, Orders.id FROM Users JOIN Orders ON Users.id = Orders.user_id;

medium

A. All users with their order IDs where user IDs match

B. All users regardless of orders

C. All orders regardless of users

D. An error due to missing WHERE clause

Solution

1. Step 1: Analyze the JOIN condition

   The query joins Users and Orders where Users.id equals Orders.user_id, linking users to their orders.

2. Step 2: Understand the SELECT output

   It selects user names and order IDs only for matching pairs, so users without orders are excluded.

3. Final Answer:

   All users with their order IDs where user IDs match -> Option A

4. Quick Check:

   JOIN with ON = matched user-orders [OK]

Hint: JOIN ON filters matching rows only [OK]

Common Mistakes:

• Thinking JOIN returns all users or all orders
• Assuming WHERE clause is mandatory for JOIN
• Confusing JOIN with UNION

4. Identify the error in this SQL query that tries to fetch all customers with their orders:

SELECT Customers.name, Orders.id FROM Customers JOIN Orders;

medium

A. No error, query is correct

B. Using SELECT instead of INSERT

C. Missing ON clause to specify join condition

D. Orders table does not exist

Solution

1. Step 1: Check JOIN syntax

   JOIN requires an ON clause to specify how tables relate; missing ON causes error or unintended Cartesian product.

2. Step 2: Confirm other parts are correct

   SELECT is correct for fetching data; assuming Orders table exists; so error is missing ON clause.

3. Final Answer:

   Missing ON clause to specify join condition -> Option C

4. Quick Check:

   JOIN needs ON clause [OK]

Hint: JOIN without ON causes errors [OK]

Common Mistakes:

• Assuming JOIN works without ON
• Confusing SELECT with INSERT
• Ignoring table existence

5. A company needs a system that supports multiple users updating customer data simultaneously without losing accuracy. Which relational database feature best supports this requirement?

hard

A. ACID transactions ensuring data consistency

B. Storing data as JSON documents

C. Using key-value pairs for fast access

D. NoSQL horizontal scaling

Solution

1. Step 1: Understand multi-user data update needs

   Multiple users updating data require mechanisms to avoid conflicts and keep data accurate.

2. Step 2: Identify relational database feature for consistency

   ACID transactions ensure atomicity, consistency, isolation, and durability, preventing data loss or corruption.

3. Final Answer:

   ACID transactions ensuring data consistency -> Option A

4. Quick Check:

   Multi-user accuracy = ACID transactions [OK]

Hint: ACID = safe multi-user updates [OK]

Common Mistakes:

• Confusing NoSQL features with relational strengths
• Thinking JSON storage ensures consistency
• Ignoring transaction properties