From January through September of 2022, Amazon Web Services (AWS) customers visited the following five Amazon DynamoDB blog posts more than all others. Use this list (starting with most visited) to see what other customers have been reading and decide what to learn next.
Amazon DynamoDB can now import Amazon S3 data into a new table by Robert McCauley and Aman Dhingra, published, August 18, 2022.
Before the launch of the DynamoDB import from Amazon S3 feature, bulk imports of data from S3 to DynamoDB meant you had to set up your own infrastructure, write code, and manage capacity. DynamoDB Specialist Solutions Architects Robert McCauley and Aman Dhingra show you how you can use DynamoDB import from S3 through the console to move large datasets from S3 into DynamoDB.
Single-table vs. multi-table design in Amazon DynamoDB by Alex DeBrie, published August 16, 2022.
AWS Hero Alex DeBrie gives you an overview of the essential differences between single- and multi-table design in DynamoDB. He starts with background information to help you understand how data is stored in DynamoDB. After providing background, Alex writes about why and when to use single-table design and when to use multi-table design.
Use parallelism to optimize querying large amounts of data in Amazon DynamoDB by Zoran Ivanovic, published April 4, 2022.
DynamoDB delivers single-digit millisecond read/write performance by default. The scan operation is useful for working with a large number of records because it accesses every item in your table, but the operation runs sequentially and isn’t optimized for performance. In this post, learn how you can use parallelism to speed up response time by splitting a single large query into multiple parallel subqueries. You also learn how to use some of the new Java 8 features to make using parallelism even more effective. In this post, Zoran Ivanovic includes modern Java concepts such as Java streams (regular, parallel, and reactive), parallelism, multithreading, and the reactive programming paradigm. He’s included code samples for both the AWS SDK for Java and AWS SDK for Java 2.x, and a walkthrough written for Java developers of all experience levels.
Archive data from Amazon DynamoDB to Amazon S3 using TTL and Amazon Kinesis integration by Bhupesh Sharma and Veerendra Nayak, published March 17, 2022.
Bhupesh Sharma and Veerendra Nayak show you how to use Amazon Kinesis integration and DynamoDB Time to Live (TTL) to design a data archiving architecture. Archiving old data helps reduce costs and meet regulatory and organization requirements governing data retention or deletion policies. DynamoDB TTL is available at no added cost and eliminates the complexity and cost of scanning tables and deleting items that you don’t want to retain. This reduces the cost of throughput and storage.
Large object storage strategies for Amazon DynamoDB by Josh Hart, published June 21, 2022.
To take advantage of the performance of DynamoDB, it’s important to develop an efficient data model. One aspect you need to consider is how to treat large objects within DynamoDB. It’s important to have a defined strategy for handling items larger than the maximum size of 400 KB to prevent unexpected behavior and to ensure your solution remains performant as it scales. In this post, Josh Hart shows you some of the options for handling large objects using DynamoDB and the benefits and disadvantages of each approach.
Let us know what topics you’d like to see covered in a blog post by reaching out to us at the @DynamoDB Twitter handle or by leaving a comment at the link below. You can find more DynamoDB blog posts in the AWS Database blog.
About the author
Darcy Jayne is a Technical Editor on the AWS DynamoDB team. She has a background in system administration and has been a technical writer and editor for multiple companies. Before joining DynamoDB, she was a member of the AWS Security Blog editorial team. Outside of work, her favorite hobbies are reading, enjoying a good meal, and spending time hiking in the Cascade Range of Washington state.
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