DynamoDB vs MongoDB: Key Differences and When to Use Each

Use DynamoDB when you need a fully managed, highly scalable NoSQL database with seamless integration on AWS and predictable performance. Choose MongoDB if you want flexible document data modeling, rich querying, and multi-cloud or on-premises deployment options.

Quick Comparison

Here is a quick side-by-side comparison of DynamoDB and MongoDB based on key factors.

Factor	DynamoDB	MongoDB
Type	Managed NoSQL key-value and document store	Document-oriented NoSQL database
Scalability	Automatic horizontal scaling with high throughput	Manual or managed scaling with sharding
Data Model	Key-value and document with strict schema on keys	Flexible JSON-like documents with dynamic schema
Querying	Primary key and secondary indexes, limited querying	Rich queries with ad-hoc filters and aggregations
Deployment	AWS cloud only	Cloud, on-premises, multi-cloud
Pricing	Pay-per-use with provisioned capacity	Free community edition, paid managed services

Key Differences

DynamoDB is a fully managed NoSQL database service by AWS designed for ultra-high scalability and low-latency performance. It uses a key-value and document data model but requires you to define primary keys upfront. It excels in workloads with predictable access patterns and integrates tightly with other AWS services.

MongoDB is a flexible document database that stores data in JSON-like documents with dynamic schemas. It supports rich querying, secondary indexes, and aggregation pipelines, making it suitable for complex queries and evolving data structures. MongoDB can be deployed on various platforms including cloud providers and on-premises.

While DynamoDB offers seamless scaling and serverless operation, MongoDB provides more query flexibility and control over deployment. Your choice depends on your application's data access patterns, infrastructure preferences, and query complexity.

Code Comparison

Here is how you insert and query a user record in DynamoDB using AWS SDK for JavaScript.

javascript

import { DynamoDBClient, PutItemCommand, GetItemCommand } from "@aws-sdk/client-dynamodb";

const client = new DynamoDBClient({ region: "us-east-1" });

async function run() {
  // Insert item
  await client.send(new PutItemCommand({
    TableName: "Users",
    Item: {
      "UserId": { S: "123" },
      "Name": { S: "Alice" },
      "Age": { N: "30" }
    }
  }));

  // Get item
  const data = await client.send(new GetItemCommand({
    TableName: "Users",
    Key: { "UserId": { S: "123" } }
  }));

  console.log(data.Item);
}

run();

Output

{ UserId: { S: '123' }, Name: { S: 'Alice' }, Age: { N: '30' } }

MongoDB Equivalent

Here is how you insert and query a user document in MongoDB using the Node.js driver.

javascript

import { MongoClient } from "mongodb";

async function run() {
  const client = new MongoClient("mongodb://localhost:27017");
  await client.connect();
  const db = client.db("testdb");
  const users = db.collection("users");

  // Insert document
  await users.insertOne({ _id: "123", name: "Alice", age: 30 });

  // Find document
  const user = await users.findOne({ _id: "123" });
  console.log(user);

  await client.close();
}

run();

Output

{ _id: '123', name: 'Alice', age: 30 }

When to Use Which

Choose DynamoDB when you want a serverless, fully managed database with automatic scaling and predictable performance on AWS. It is ideal for applications with simple key-value access patterns, such as gaming leaderboards, session stores, or IoT data.

Choose MongoDB when your application requires flexible schemas, complex queries, or multi-cloud/on-premises deployment. It suits content management, catalogs, and applications needing rich querying and aggregation.

Key Takeaways

DynamoDB is best for fully managed, scalable AWS-native NoSQL workloads with simple access patterns.

MongoDB offers flexible document schemas and rich queries for complex data and multi-environment deployment.

Use DynamoDB for serverless apps needing high throughput and low latency on AWS.

Use MongoDB when you need advanced querying and schema flexibility outside AWS or on-premises.

Your choice depends on your app’s data model, query needs, and deployment preferences.