Why database scaling handles data growth in HLD - Challenge Your Understanding

Challenge - 5 Problems

🧠 Conceptual

intermediate

How does vertical scaling improve database capacity?

Imagine you have a small shop and you want to serve more customers. You decide to buy a bigger cash register that can handle more transactions at once. In database terms, this is called vertical scaling.

Which of the following best explains how vertical scaling helps handle data growth?

A By creating multiple copies of the database to improve read speed but not increase storage capacity.

B By splitting the database into smaller parts and storing them on different servers to distribute the load.

C By adding more powerful hardware like CPU and RAM to the existing database server to handle more data and queries.

D By compressing the data to reduce its size without changing the hardware.

💡 Hint

Think about upgrading the size of one machine versus adding more machines.

Vertical scaling means making one server stronger by adding resources like CPU, RAM, or storage. This helps the database handle more data and queries on the same machine.

❓ Architecture

intermediate

What is horizontal scaling in databases?

Suppose your shop is growing fast and one big cash register is not enough. You decide to open more cash registers to serve customers in parallel. This is similar to horizontal scaling in databases.

Which option best describes horizontal scaling?

A Upgrading the existing server with better hardware components.

B Adding more servers to share the database load by splitting data across them.

C Backing up the database regularly to prevent data loss.

D Using a faster network connection to speed up data transfer.

💡 Hint

Think about adding more machines instead of making one machine bigger.

Horizontal scaling means adding more servers to distribute the database load. Data is split or replicated across these servers to handle more users and data volume.

❓ scaling

advanced

Which challenge is unique to horizontal scaling compared to vertical scaling?

When scaling databases, vertical and horizontal scaling have different challenges. Which of the following is a challenge unique to horizontal scaling?

A Managing data consistency across multiple servers.

B Upgrading the CPU and memory of a single server.

C Increasing disk space on the existing server.

D Reducing the size of database indexes.

💡 Hint

Think about what happens when data is spread over many machines.

Horizontal scaling involves multiple servers, so keeping data consistent and synchronized across them is a key challenge. Vertical scaling does not have this issue as data stays on one machine.

❓ tradeoff

advanced

What is a tradeoff when choosing vertical scaling over horizontal scaling?

Choosing between vertical and horizontal scaling depends on tradeoffs. Which of the following is a tradeoff when choosing vertical scaling?

A Limited by the maximum hardware capacity of a single server, making future growth harder.

B Complexity in splitting data and queries across many servers.

C Higher network latency due to data being spread over multiple machines.

D Need to manage multiple database instances and synchronization.

💡 Hint

Think about the limits of one machine versus many machines.

Vertical scaling is limited by how powerful one machine can be. Once it reaches its max capacity, you cannot scale further without switching to horizontal scaling.

❓ estimation

expert

Estimate the number of servers needed for horizontal scaling

Your database currently runs on one server handling 1000 queries per second. You expect traffic to grow to 10,000 queries per second. Each server can handle 1500 queries per second before performance degrades.

How many servers do you need to handle the expected load with horizontal scaling?

A 5 servers

B 6 servers

C 8 servers

D 7 servers

💡 Hint

Divide total expected queries by capacity per server, then round up.

10,000 queries / 1,500 queries per server = 6.66 servers. Since you cannot have a fraction of a server, round up to 7 servers.