What Is DynamoDB CDC? Methods, Benefits & Use Cases

Does your organization rely on real-time analytics for decision-making, or is your product itself a real-time application? Either way, systems majorly fail when the database can’t keep up. That’s why Amazon introduced DynamoDB, a serverless, cloud database that tracks data modifications in real time through change data capture(CDC). 

In this article, we’ll discuss DynamoDB CDC, how it works, the steps to implement it, and best practices. 

Overview of DynamoDB

DynamoDB is a No-SQL, fully managed database that stores key-value pairs and document data. Provided by AWS, it’s fully cloud—there’s no on-premise option—offering all the advantages of online storage. 

The primary purpose of DynamoDB is to eliminate operational complexities of relational databases while scaling effortlessly. Unlike traditional databases, you don’t need to handle infrastructure manually, instead it automatically scales up or down with changing demands. Moreover, DynamoDB distributes data across servers, offering high performance at scale. 

What Is DynamoDB Change Data Capture (CDC)?

CDC is the process of identifying changes made to a database and reflecting them in other systems, tools, and applications. This ensures the data syncs everywhere. 

Keeping it accurate for compliance purposes as well. 

What Are the Key Benefits of Implementing CDC for DynamoDB?

• Real-time Data Integration: DynamoDB CDC facilitates real-time database integration with other systems, applications, and warehouses within the organization. By ensuring the latest data is available across all systems, it allows users to make informed decisions.
• Best For Event Data: CDC is great for events or quickly moving data. No matter how often the changes are, it ensures databases and other systems always have the most up-to-date information.
• Minimal Load on DynamoDB: Unlike batch processing, which schedules full-table scans at intervals to detect changes, it tracks only incremental operations, such as insert, update, and delete. This eliminates unnecessary reads and writes, minimizing I/O operations and load on the database.
• Improved Analytics: Businesses rely on analytics and machine learning for decision-making. CDC enables seamless integration with Amazon S3, Redshift, or Elasticsearch, ensuring databases receive fresh data for accurate analytics predictions.
• Ensures Compliance: CDC captures and logs every data change occurred. This simplifies auditing and helps maintain standard compliance regulations. 

What Are the Different Methods For Implementing Change Data Capture With DynamoDB? 

DynamoDB offers two streaming approaches to implement CDC: DynamoDB streams and Kinesis data streams. 

Change Data Capture for DynamoDB Streams

When you enable a DynamoDB stream on a table, it records each data modification and appends it to a log, which is accessible for up to 24 hours. Applications can access this log in real time and view what’s updated. 

Whenever an item is updated in a table, DynamoDB streams writes a stream record to the log file. Each record includes the primary key of the modified item, making it easily accessible. You can configure the stream record to store: 

• Keys only – just the primary key
• New image – the updated item
• Old image – the item before modification
• Both new and old images – before and after modification

Key Features:

• It stores the time-ordered flow of information about the modifications. That is, for each modified item, the stream record appears in the same sequence as the modifications happened. 
• Datastreams automatically ignore commands that don’t alter the data. For example, if a record is overwritten with the same value, DynamoDB Streams does not create a stream record, preventing unnecessary logs.
• Each data modification is captured only once with a unique stream record, eliminating duplication. 

How to Enable Data Streams on a DynamoDB Table?

Step 1: Sign in to the AWS management console and type “dynamodb” in the search bar.

Step 2: Select “Tables” from the left menu bar and select the table on which you want to enable 

streams.

Step 3: Click on the ‘Exports and Streams’ tab.

Step 4: As shown in the image, select the “Turn on” button next to “Amazon Kinesis data stream details” instead of “DynamoDB stream details.”

Step 5: Choose from the four available options and click ‘Turn on stream.’

That’s it, DynamoDB streams is enabled on the chosen table. 

Amazon Kinesis Data Streams for DynamoDB

Kinesis data streams tracks item-level modifications in a DynamoDB table and writes them to a Kinesis data stream. Your applications can reach these streams just like any other record. 

Unlike DynamoDB streams, Kinesis streams can contain changes in any order, and update streams can appear more than once. However, you can use the ‘ApproximateCreationDateTime’ attribute to identify duplicates or the order of data modifications. 

Follow the first three steps as mentioned in the above process. 

Step 4: Select the turn on button next to “Amazon Kinesis data stream details” instead of “DynamoDB stream details” as shown in the image.

Step 5: Click “Create new” next to the Destination kinesis data stream. 

Step 6: Enter the required details and click ‘Create data stream.’

You’ve now enabled Kinesis data streams on your DynamoDB table. 

Implementing CDC, either by DynamoDB data streams or Kinesis data streams, requires you to manually manage everything, from implementation to monitoring. Moreover, manual errors can lead to inconsistent data across systems. Hevo automates the entire process, seamlessly copying data from DynamoDB to various destinations while replicating modifications in real time. Here is a guide to connecting Hevo and DynamoDB. 

What Are the Common Use Cases of Setting Up CDC with DynamoDB? 

Fin-tech

CDC updates the data as soon as a transaction happens. This helps ensure atomicity in financial transactions. Moreover, with real-time visibility into spendings, systems can quickly identify suspicious transactions, preventing potential fraud. 

E-commerce

Accurate inventory management is critical for e-commerce businesses—it impacts every department, from stock availability and shipments to discount strategies and digital storefront updates. So, capturing it in real-time is important for efficient business operations.

CDC in DynamoDb facilitates real-time inventory tracking. For example, the inventory data increases as soon as it receives returns and shrinks whenever a sale happens, providing real-time visibility for better decision-making. 

Social Media

Want to notify your followers the moment you upload a post or status on Instagram? CDC helps it happen. It captures any data modifications instantly and triggers the required action, sending notifications in this case.  

Supply Chain 

When you turn on CDC for transportation data, it keeps systems in sync with real-time traffic updates, optimizing for better routes. Additionally, consistent and up-to-date data across suppliers, warehouses, and retailers leads to optimized shipping operations. 

Best Practices & Challenges in Implementing DynamoDB CDC

• Frequent updates: If your data often updates, CDC writes numerous logs, making it difficult to manage high-throughput applications through DynamoDB streams.
  Best practice: For high-volume event data, implement Kinesis Data Streams with DynamoDB, which is designed to process scalable and high-throughput event data. 

• Costs: CDC processing can be expensive due to Lambda invocations, Kinesis throughput, and storage costs.
  Best practice: Implement batch processing instead of processing individual events. Regularly monitor your costs using AWS Cost Explorer or its alternatives. 

• Cold start in AWS Lambda: AWS Lambda enables real-time event processing in CDC data updates. When DynamoDB captures data modifications, Lambda triggers events like notifying external systems or updating downstream applications. However, Lambda can introduce latency if it’s idle when a sudden data update occurs—this happens due to cold starts (the time taken to initialize a function when it hasn’t been used recently).
  Best practice: Keep backup Lambda instances always running to handle sudden events through provisioned concurrency. Here is a more detailed guide on using DynamoDB streams with Lambda functions.  

Conclusion

In this tutorial, we explored the fundamentals of DynamoDB change data capture, its key benefits, and different approaches to implementing it. Throughout the tutorial, we discussed steps to implement CDC in DynamoDB through two popular methods: DynamoDB streams and Kinesis data streams. We’ve also explored how each method works.

As you use the DynamoDB database, consider connecting it to external systems using Hevo to automate data movement and replication. 

Want to take Hevo for a spin? Sign up for a 14-day free trial and experience the feature-rich Hevo suite firsthand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

FAQs