DynamoDB vs MongoDB vs Cassandra - Performance Comparison

Time Complexity: DynamoDB vs MongoDB vs Cassandra

O(1)

Understanding Time Complexity

When working with databases like DynamoDB, MongoDB, and Cassandra, it's important to understand how their operations scale as data grows.

We want to know how the time to perform common tasks changes when the amount of data increases.

Scenario Under Consideration

Analyze the time complexity of a simple read operation in DynamoDB.

const params = {
  TableName: "Users",
  Key: { "UserId": "123" }
};
const result = await dynamodb.get(params).promise();
    

This code fetches a single item by its primary key from a DynamoDB table.

Identify Repeating Operations

Look for loops or repeated work inside the operation.

• Primary operation: Single key lookup in a distributed hash table.
• How many times: Exactly once per request, no loops over data.

How Execution Grows With Input

As the number of items in the table grows, the time to get one item stays about the same.

Input Size (n)	Approx. Operations
10	1 lookup
100	1 lookup
1000	1 lookup

Pattern observation: The time does not increase with more data because the lookup uses a key directly.

Final Time Complexity

Time Complexity: O(1)

This means the time to get an item by key stays constant no matter how big the table is.

Common Mistake

[X] Wrong: "Getting an item by key takes longer as the table grows because there are more items to search."

[OK] Correct: DynamoDB uses a hash-based index, so it goes directly to the item without scanning the whole table.

Interview Connect

Understanding how different databases handle data lookup helps you choose the right tool and explain your choices clearly in conversations.

Self-Check

What if we changed the query to scan the entire table instead of using a key? How would the time complexity change?

Practice

1. Which database is best known for automatic scaling and simple key-value access?

easy

A. Cassandra

B. DynamoDB

C. MongoDB

D. MySQL

Solution

1. Step 1: Understand DynamoDB's core feature

   DynamoDB is designed for simple key-value access and automatic scaling.

2. Step 2: Compare with other databases

   MongoDB focuses on flexible document storage, Cassandra on high availability for huge data.

3. Final Answer:

   DynamoDB -> Option B

4. Quick Check:

   Automatic scaling + key-value = DynamoDB [OK]

Hint: Automatic scaling with key-value means DynamoDB [OK]

Common Mistakes:

• Confusing MongoDB's flexible documents with key-value simplicity
• Thinking Cassandra automatically scales like DynamoDB
• Choosing MySQL which is relational, not key-value

2. Which of the following is the correct way to describe MongoDB's data model?

easy

A. Column-family store with automatic partitioning

B. Simple key-value pairs with fixed schema

C. Flexible document storage with rich queries

D. Relational tables with strict schema

Solution

1. Step 1: Identify MongoDB's data model

   MongoDB stores data as flexible JSON-like documents allowing rich queries.

2. Step 2: Eliminate other options

   Column-family store describes Cassandra, key-value with fixed schema fits DynamoDB less, relational tables fit SQL databases.

3. Final Answer:

   Flexible document storage with rich queries -> Option C

4. Quick Check:

   MongoDB = flexible documents + rich queries [OK]

Hint: MongoDB = flexible JSON documents + rich queries [OK]

Common Mistakes:

• Confusing MongoDB with Cassandra's column-family model
• Thinking MongoDB uses fixed schema like relational DB
• Mixing key-value with document storage

3. Given a large dataset requiring high availability and fast writes across multiple data centers, which database is most suitable?

medium

A. MongoDB

B. DynamoDB

C. SQLite

D. Cassandra

Solution

1. Step 1: Analyze requirements for high availability and multi-datacenter writes

   Cassandra is designed for huge data with high availability and multi-region replication.

2. Step 2: Compare other options

   MongoDB supports replication but less optimized for huge scale multi-datacenter writes; DynamoDB is scalable but less focused on multi-datacenter writes; SQLite is local and not distributed.

3. Final Answer:

   Cassandra -> Option D

4. Quick Check:

   High availability + multi-datacenter = Cassandra [OK]

Hint: Huge data + multi-region writes = Cassandra [OK]

Common Mistakes:

• Choosing DynamoDB for multi-datacenter writes
• Confusing SQLite as distributed database
• Assuming MongoDB handles huge multi-region writes best

4. You try to use MongoDB's flexible document queries on DynamoDB but get errors. What is the likely cause?

medium

A. DynamoDB does not support flexible document queries like MongoDB

B. DynamoDB requires SQL syntax for queries

C. MongoDB uses column-family data model incompatible with DynamoDB

D. DynamoDB only supports relational tables

Solution

1. Step 1: Understand query capabilities of DynamoDB

   DynamoDB supports key-value and simple queries but not rich flexible document queries like MongoDB.

2. Step 2: Eliminate incorrect causes

   DynamoDB does not use SQL syntax, is not column-family, and is not relational.

3. Final Answer:

   DynamoDB does not support flexible document queries like MongoDB -> Option A

4. Quick Check:

   DynamoDB lacks MongoDB's flexible queries [OK]

Hint: DynamoDB lacks MongoDB's rich document query support [OK]

Common Mistakes:

• Assuming DynamoDB uses SQL syntax
• Confusing data models between MongoDB and Cassandra
• Thinking DynamoDB supports relational tables

5. You need a database for an app that requires flexible JSON documents, automatic scaling, and global availability. Which approach best fits this need?

hard

A. Use DynamoDB with JSON support and global tables

B. Use MongoDB with sharding and replica sets only

C. Use Cassandra with column-family tables and no JSON support

D. Use SQLite with local JSON extensions

Solution

1. Step 1: Identify features needed

   The app needs flexible JSON documents, automatic scaling, and global availability.

2. Step 2: Match features to databases

   DynamoDB supports JSON documents, automatic scaling, and global tables for availability. MongoDB supports JSON but global availability requires extra setup and scaling is manual. Cassandra lacks native JSON support and SQLite is local only.

3. Final Answer:

   Use DynamoDB with JSON support and global tables -> Option A

4. Quick Check:

   JSON + auto scale + global = DynamoDB [OK]

Hint: DynamoDB global tables + JSON = best for scaling + availability [OK]

Common Mistakes:

• Choosing MongoDB without considering scaling complexity
• Ignoring Cassandra's lack of JSON support
• Selecting SQLite which is not distributed