Integrating with DynamoDB
Connect Lambda functions to Amazon DynamoDB, a fully managed NoSQL database, for high-performance, scalable data storage and retrieval in serverless applications.
Integrating with DynamoDB is a free Serverless AWS Lambda Development lesson on CoddyKit — lesson 1 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Serverless AWS Lambda Development learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Lambda Meets DynamoDB
Welcome! In this lesson, we'll connect the power of serverless AWS Lambda with Amazon DynamoDB, a super-fast and flexible NoSQL database.
This combination is perfect for building scalable, high-performance applications without managing servers or database infrastructure.
DynamoDB: NoSQL in a Nutshell
Amazon DynamoDB is a fully managed, serverless NoSQL database. Unlike traditional SQL databases, it uses a key-value and document data model.
- Tables: Similar to SQL tables, but hold items.
- Items: Like rows in SQL, but can have different attributes.
- Attributes: Like columns, but flexible (no fixed schema).
- Primary Key: Uniquely identifies each item. Can be a simple Partition Key or a composite Partition Key + Sort Key.
Setting Up Your DynamoDB Table
Before Lambda can interact with DynamoDB, you need a table. You can create one easily in the AWS Management Console.
When creating, you'll define a Primary Key. For example, an id attribute as a Partition Key is common for simple lookups.
Giving Lambda DynamoDB Access
For your Lambda function to talk to DynamoDB, it needs permission. This is managed via an IAM Role attached to your Lambda function.
You'll need to grant policies like dynamodb:PutItem, dynamodb:GetItem, etc., to specific tables for secure, granular access. For simplicity in learning, AmazonDynamoDBFullAccess might be used initially, but always prefer least privilege in production.
Writing Data: The PutItem Op
The PutItem operation is used to add a new item to a table or replace an existing item if an item with the same primary key already exists.
Try running this example to see how to add an item. We're using a mock AWS SDK for local execution.
// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
DocumentClient: function() {
return {
put: (params) => ({
promise: () => {
console.log("MOCK: Put item to table '" + params.TableName + "':", params.Item);
return Promise.resolve({ success: true, item: params.Item });
}
})
};
}
};
// Simulate the Lambda handler function
async function handler(event) {
const ddb = new mockDynamoDB.DocumentClient();
const params = {
TableName: "MyUsersTable", // Replace with your table name
Item: {
id: event.userId,
name: event.userName,
email: event.userEmail
}
};
try {
const data = await ddb.put(params).promise();
console.log("Operation successful (mock):", data);
return { statusCode: 200, body: JSON.stringify(data) };
} catch (err) {
console.error("Operation failed (mock):", err);
return { statusCode: 500, body: JSON.stringify(err) };
}
}
// Entry point for CoddyKit's runnable environment
async function main() {
console.log("Running simulated PutItem operation...");
const testEvent = {
userId: "user123",
userName: "Alice",
userEmail: "alice@example.com"
};
await handler(testEvent);
}
main();Understanding the PutItem Code
In the example, we're using DynamoDB.DocumentClient() to simplify interactions with DynamoDB, as it handles data types automatically.
TableName: The name of your DynamoDB table.Item: A JavaScript object representing the data you want to store. Each key-value pair is an attribute.promise(): Used to handle the asynchronous nature of AWS SDK calls.
Reading Data: The GetItem Op
To retrieve a single item from your table, you use the GetItem operation. You must provide the full Primary Key of the item you want to fetch.
Run this code to see how to get an item back.
// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
DocumentClient: function() {
return {
get: (params) => ({
promise: () => {
console.log("MOCK: Get item from table '" + params.TableName + "' with Key:", params.Key);
// Simulate finding an item with id 'user123'
if (params.Key.id === "user123") {
return Promise.resolve({ Item: { id: "user123", name: "Alice", email: "alice@example.com" } });
}
return Promise.resolve({ Item: null }); // Item not found
}
})
};
}
};
// Simulate the Lambda handler function
async function handler(event) {
const ddb = new mockDynamoDB.DocumentClient();
const params = {
TableName: "MyUsersTable", // Replace with your table name
Key: {
id: event.userId // The primary key to retrieve
}
};
try {
const data = await ddb.get(params).promise();
console.log("Retrieved item (mock):", data.Item);
return { statusCode: 200, body: JSON.stringify(data.Item) };
} catch (err) {
console.error("Operation failed (mock):", err);
return { statusCode: 500, body: JSON.stringify(err) };
}
}
// Entry point for CoddyKit's runnable environment
async function main() {
console.log("Running simulated GetItem operation...");
const testEvent = {
userId: "user123" // ID of the item to retrieve
};
await handler(testEvent);
}
main();Updating Data: The UpdateItem Op
The UpdateItem operation modifies existing attributes of an item or adds new attributes if they don't exist. It's more efficient than reading, modifying, and then putting the whole item back.
This example updates the email for an existing user.
// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
DocumentClient: function() {
return {
update: (params) => ({
promise: () => {
console.log("MOCK: Update item in table '" + params.TableName + "' with Key:", params.Key);
console.log("MOCK: Update Expression:", params.UpdateExpression, "Values:", params.ExpressionAttributeValues);
return Promise.resolve({ Attributes: { id: params.Key.id, email: "updated@example.com" } });
}
})
};
}
};
// Simulate the Lambda handler function
async function handler(event) {
const ddb = new mockDynamoDB.DocumentClient();
const params = {
TableName: "MyUsersTable", // Replace with your table name
Key: {
id: event.userId // Primary key of the item to update
},
UpdateExpression: "set email = :e",
ExpressionAttributeValues: {
":e": event.newEmail
},
ReturnValues: "UPDATED_NEW" // Return the new values of updated attributes
};
try {
const data = await ddb.update(params).promise();
console.log("Updated item (mock):", data.Attributes);
return { statusCode: 200, body: JSON.stringify(data.Attributes) };
} catch (err) {
console.error("Operation failed (mock):", err);
return { statusCode: 500, body: JSON.stringify(err) };
}
}
// Entry point for CoddyKit's runnable environment
async function main() {
console.log("Running simulated UpdateItem operation...");
const testEvent = {
userId: "user123",
newEmail: "alice.new@example.com"
};
await handler(testEvent);
}
main();Deleting Data: The DeleteItem Op
When you no longer need an item, you can remove it using the DeleteItem operation. Just like GetItem, you must specify the full primary key of the item to delete.
Be careful with deletions, as they are permanent!
// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
DocumentClient: function() {
return {
delete: (params) => ({
promise: () => {
console.log("MOCK: Delete item from table '" + params.TableName + "' with Key:", params.Key);
return Promise.resolve({ success: true });
}
})
};
}
};
// Simulate the Lambda handler function
async function handler(event) {
const ddb = new mockDynamoDB.DocumentClient();
const params = {
TableName: "MyUsersTable", // Replace with your table name
Key: {
id: event.userId // Primary key of the item to delete
}
};
try {
const data = await ddb.delete(params).promise();
console.log("Item deleted successfully (mock).");
return { statusCode: 200, body: JSON.stringify(data) };
} catch (err) {
console.error("Operation failed (mock):", err);
return { statusCode: 500, body: JSON.stringify(err) };
}
}
// Entry point for CoddyKit's runnable environment
async function main() {
console.log("Running simulated DeleteItem operation...");
const testEvent = {
userId: "user123" // ID of the item to delete
};
await handler(testEvent);
}
main();Quick Check: DynamoDB Actions
You've learned about basic DynamoDB operations. Let's test your understanding!
Recap: Lambda + DynamoDB
Great job! You've learned how to integrate AWS Lambda with Amazon DynamoDB for powerful serverless applications.
- DynamoDB provides a scalable NoSQL database.
- Lambda functions need IAM permissions to interact with DynamoDB tables.
- You can perform common operations like
PutItem(create/replace),GetItem(read),UpdateItem(modify), andDeleteItem(remove).
This integration is fundamental for building dynamic, event-driven serverless backends!
Frequently asked questions
Is the “Integrating with DynamoDB” lesson free?
Yes — the full text of “Integrating with DynamoDB” is free to read here on the web, and the Serverless AWS Lambda Development course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Serverless AWS Lambda Development course, upgrade to CoddyKit PRO.
What will I learn in “Integrating with DynamoDB”?
Connect Lambda functions to Amazon DynamoDB, a fully managed NoSQL database, for high-performance, scalable data storage and retrieval in serverless applications. You practise Serverless AWS Lambda Development with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Serverless AWS Lambda Development?
No prior experience is required. Serverless AWS Lambda Development on CoddyKit is structured for beginners through advanced learners; this is — lesson 1 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Integrating with DynamoDB” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Serverless AWS Lambda Development lesson?
Yes. Every Serverless AWS Lambda Development lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Integrating with DynamoDB
- S3 for File Storage and Events
- Choosing the Right Data Store
- Caching with Amazon ElastiCache and DAX