AWS Lambda is a serverless compute service that runs your code in response to events and automatically manages the underlying compute resources for you. It is a part of the Amazon Web Services (AWS) cloud platform and enables you to run code without provisioning or managing servers.
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It is a part of the Amazon Web Services (AWS) cloud platform and allows you to store and retrieve data at any scale.
How to connect?
In this diagram, the client makes a request to the Lambda function, which triggers the function to execute. The Lambda function uses AWS.DynamoDB client in the AWS SDK for JavaScript in Node.js to connect to DynamoDB and perform various operations on the data stored in the DynamoDB table, such as inserting, updating, or deleting items. The Lambda function can then return the data from DynamoDB to the client as a response to the request.
To connect an AWS Lambda function to Amazon DynamoDB, you can use AWS.DynamoDB client in the AWS SDK for JavaScript in Node.js.
Here’s an example of how you can use AWS.DynamoDB client to put an item into a DynamoDB table from a Lambda function:
const AWS = require('aws-sdk');
exports.handler = async (event) => {
const dynamoDb = new AWS.DynamoDB();
const params = {
TableName: 'my-table',
Item: {
'id': {S: '123'},
'name': {S: 'John'},
'age': {N: '35'},
}
};
try {
await dynamoDb.putItem(params).promise();
return { statusCode: 200, body: 'Item added to DynamoDB' };
} catch (error) {
return { statusCode: 500, body: error.message };
}
};
In this example, the putItem method is used to add an item to the my-table DynamoDB table. The Item parameter specifies the attributes of the item to be added, and the data types of each attribute (e.g. S for string, N for number).
To use AWS.DynamoDB client, you’ll need to configure the AWS SDK with your AWS access keys. You can do this either by using an AWS Identity and Access Management (IAM) role that has permission to access DynamoDB or by providing your access keys directly in your code.
It’s also worth noting that AWS.DynamoDB client has many other methods that you can use to perform various operations on DynamoDB tables, such as getting an item, updating an item, deleting an item, and querying a table. You can find more information about these methods in the AWS SDK for JavaScript in Node.js documentation.
Keys in Dynamo DB?
In Amazon DynamoDB, there are two types of indexing keys that you can use to index your data: primary keys and secondary indexes.
Primary keys:
A primary key is a unique identifier for an item in a DynamoDB table. Every item in a table must have a primary key, and the primary key must be unique across all items in the table. There are two types of primary keys in DynamoDB:
- Partition key: A simple primary key, composed of a single attribute. The partition key value is used to determine which partition the item is stored in.
- Partition key and sort key: A composite primary key, composed of two attributes. The partition key value determines the partition that the item is stored in, and the sort key is used to order items within a partition.
Secondary indexes:
A secondary index is an index that allows you to query your data based on non-key attributes. You can create one or more secondary indexes on a table, and each secondary index can have a different primary key structure than the table itself. There are two types of secondary indexes in DynamoDB:
- Global secondary index: An index with a primary key that has the same or a different primary key schema than the table. A global secondary index allows you to query the entire table, across all partitions.
- Local secondary index: An index that has the same partition key as the table, but a different sort key. A local secondary index allows you to query within a single partition of the table.
Using primary keys and secondary indexes, you can design your DynamoDB tables to support fast and efficient querying of your data. You can choose the right indexing strategy based on your application’s read and write patterns, and scale your tables horizontally to support very high read and write throughput.
What is Amazon DynamoDB Accelerator (DAX)?
Amazon DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that sits in front of a DynamoDB table and speeds up read and write access to the table. DAX improves the performance of your DynamoDB table by caching frequently accessed data in memory, so that it can be retrieved quickly with minimal or no delay.
DAX is designed to scale with your DynamoDB table, so you can easily add or remove cache nodes as needed to meet the performance and capacity requirements of your applications. You can use DAX with DynamoDB tables of any size, and it supports both read- and write-through caching, which means that it can cache data from both read and write requests.
By using DAX with your DynamoDB table, you can significantly improve the performance and scalability of your applications. DAX can handle millions of requests per second with low latencies, and it can scale horizontally to support very high read and write throughput. It is a great choice for applications that require fast and predictable access to data, and can help you offload read and write traffic from your DynamoDB table, reducing the load on your table and helping you scale your applications more effectively.