When to use SQL vs NoSQL in HLD - Architecture Patterns Compared

System Overview - When to use SQL vs NoSQL

This system helps decide when to use SQL or NoSQL databases based on application needs. It guides users by analyzing data structure, scalability, consistency, and query complexity requirements.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  +---------------------+
  |                     |
SQL Service         NoSQL Service
  |                     |
SQL Database       NoSQL Database
  |                     |
Cache               Cache

Components

User

client

Sends requests to decide database type

Load Balancer

load_balancer

Distributes incoming requests evenly

API Gateway

api_gateway

Routes requests to SQL or NoSQL service based on criteria

SQL Service

service

Handles requests needing structured, relational data

NoSQL Service

service

Handles requests needing flexible, scalable data storage

SQL Database

database

Stores structured data with strong consistency

NoSQL Database

database

Stores unstructured or semi-structured data with flexible schema

Cache

cache

Speeds up frequent data reads for both databases

Request Flow - 17 Hops

User → Load Balancer

Load Balancer → API Gateway

API Gateway → SQL Service or NoSQL Service

SQL Service → Cache

Cache → SQL Service

SQL Service → SQL Database

SQL Database → SQL Service

SQL Service → Cache

SQL Service → API Gateway

NoSQL Service → Cache

Cache → NoSQL Service

NoSQL Service → NoSQL Database

NoSQL Database → NoSQL Service

NoSQL Service → Cache

NoSQL Service → API Gateway

API Gateway → Load Balancer

Load Balancer → User

Failure Scenario

Component Fails:SQL Database

Impact:SQL Service cannot retrieve or store structured data; cache may serve stale reads

Mitigation:Use database replication and failover; cache serves read requests temporarily; writes are queued or rejected until recovery

Architecture Quiz - 3 Questions

Which component decides whether to use SQL or NoSQL service?

A API Gateway

B Load Balancer

C Cache

D User

Design Principle

This architecture shows how to route requests to SQL or NoSQL databases based on data needs. It uses caching to improve performance and includes failover strategies for database failures, demonstrating scalable and reliable design.

Practice

1. Which type of database is best suited for data with a fixed schema and strong relationships between tables?

easy

A. Flat file storage

B. NoSQL database

C. SQL database

D. In-memory cache

Solution

1. Step 1: Understand data structure needs

   Data with fixed schema and strong relationships fits well with structured tables.

2. Step 2: Match database type to structure

   SQL databases use tables and enforce schema, ideal for such data.

3. Final Answer:

   SQL database -> Option C

4. Quick Check:

   Structured data = SQL database [OK]

Hint: Fixed schema and relations? Choose SQL [OK]

Common Mistakes:

• Choosing NoSQL for strictly structured data
• Confusing flat files with databases
• Assuming in-memory cache stores persistent data

2. Which of the following is the correct way to describe NoSQL databases?

easy

A. They always use tables with fixed columns

B. They are designed for flexible, schema-less data storage

C. They require strict ACID transactions for all operations

D. They cannot handle large volumes of data

Solution

1. Step 1: Identify NoSQL characteristics

   NoSQL databases allow flexible, schema-less data models.

2. Step 2: Eliminate incorrect options

   They do not require fixed tables or strict ACID for all operations and can handle large data.

3. Final Answer:

   They are designed for flexible, schema-less data storage -> Option B

4. Quick Check:

   NoSQL = flexible schema [OK]

Hint: No fixed schema? NoSQL fits best [OK]

Common Mistakes:

• Thinking NoSQL always uses tables
• Assuming NoSQL can't scale
• Confusing ACID requirements with SQL only

3. Consider a social media app storing user posts that can have varying fields like text, images, or videos. Which database type will likely handle this data best?

medium

A. SQL database with fixed tables

B. CSV files for storage

C. Relational database with strict schema

D. NoSQL document database

Solution

1. Step 1: Analyze data variability

   User posts have varying fields, so schema flexibility is needed.

2. Step 2: Choose database type matching flexibility

   NoSQL document databases store flexible, nested data well.

3. Final Answer:

   NoSQL document database -> Option D

4. Quick Check:

   Variable fields = NoSQL document DB [OK]

Hint: Varying fields? Use NoSQL document DB [OK]

Common Mistakes:

• Choosing fixed-schema SQL for flexible data
• Using CSV which lacks query power
• Confusing relational DB with NoSQL

4. A developer tries to store rapidly changing sensor data with a fixed schema in a SQL database but faces performance issues. What is the likely cause and best fix?

medium

A. Fixed schema causes overhead; use a NoSQL database for flexibility

B. SQL databases are slow; switch to CSV files

C. Sensor data is small; use in-memory cache only

D. NoSQL databases cannot handle sensor data

Solution

1. Step 1: Identify problem with fixed schema and rapid changes

   Fixed schema in SQL causes overhead with frequent schema updates or inserts.

2. Step 2: Recommend flexible schema database

   NoSQL databases handle rapid, flexible data better, improving performance.

3. Final Answer:

   Fixed schema causes overhead; use a NoSQL database for flexibility -> Option A

4. Quick Check:

   Rapid changes + fixed schema = use NoSQL [OK]

Hint: Rapid, flexible data? NoSQL is better [OK]

Common Mistakes:

• Switching to CSV which lacks performance
• Assuming NoSQL can't handle sensor data
• Ignoring schema flexibility importance

5. You are designing a global e-commerce platform that needs to store user profiles, product catalogs, and handle millions of transactions per day. Which database strategy is best?

hard

A. Use SQL for transactions and NoSQL for product catalogs and user profiles

B. Use only SQL for all data to keep consistency

C. Use only NoSQL for all data to maximize flexibility

D. Use flat files for product catalogs and SQL for transactions

Solution

1. Step 1: Analyze data types and needs

   Transactions require strong consistency (SQL), catalogs and profiles need flexibility and scale (NoSQL).

2. Step 2: Combine database types for best fit

   Using SQL for transactions ensures ACID compliance; NoSQL handles flexible, large-scale data efficiently.

3. Final Answer:

   Use SQL for transactions and NoSQL for product catalogs and user profiles -> Option A

4. Quick Check:

   Mixed data needs = hybrid SQL + NoSQL [OK]

Hint: Mix SQL for transactions, NoSQL for flexible data [OK]

Common Mistakes:

• Using only SQL limits flexibility and scale
• Using only NoSQL risks transaction consistency
• Using flat files lacks query and scale support