AWS Big Data Blog
Category: Amazon DynamoDB
Build seamless data streaming pipelines with Amazon Kinesis Data Streams and Amazon Data Firehose for Amazon DynamoDB tables
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. The global wearables market […]
Build a data lake using Amazon Kinesis Data Streams for Amazon DynamoDB and Apache Hudi
August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. July 2023: This post was reviewed for accuracy. Amazon DynamoDB helps you capture high-velocity data such as clickstream data to form customized user profiles and online order […]
Building a real-time notification system with Amazon Kinesis Data Streams for Amazon DynamoDB and Amazon Kinesis Data Analytics for Apache Flink
August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Amazon DynamoDB helps you capture high-velocity data such as clickstream data to form customized user profiles and Internet of Things (IoT) data so that you can develop […]
Detect change points in your event data stream using Amazon Kinesis Data Streams, Amazon DynamoDB and AWS Lambda
The success of many modern streaming applications depends on the ability to sequentially detect each change as soon as possible after it occurs, while continuing to monitor the data stream as it evolves. Applications of change point detection range across genomics, marketing, and finance, to name a few. In genomics, change point detection can help […]
Unified serverless streaming ETL architecture with Amazon Kinesis Data Analytics
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Businesses across the world […]
How to delete user data in an AWS data lake
General Data Protection Regulation (GDPR) is an important aspect of today’s technology world, and processing data in compliance with GDPR is a necessity for those who implement solutions within the AWS public cloud. One article of GDPR is the “right to erasure” or “right to be forgotten” which may require you to implement a solution […]
Enhancing customer safety by leveraging the scalable, secure, and cost-optimized Toyota Connected Data Lake
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Toyota Motor Corporation (TMC), a global automotive manufacturer, has made “connected cars” a core priority as part of its broader transformation from an auto company to a mobility company. In recent years, […]
How Siemens built a fully managed scheduling mechanism for updates on Amazon S3 data lakes
Siemens is a global technology leader with more than 370,000 employees and 170 years of experience. To protect Siemens from cybercrime, the Siemens Cyber Defense Center (CDC) continuously monitors Siemens’ networks and assets. To handle the resulting enormous data load, the CDC built a next-generation threat detection and analysis platform called ARGOS. ARGOS is a […]
How FactSet automated exporting data from Amazon DynamoDB to Amazon S3 Parquet to build a data analytics platform
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. This is a guest post by Arvind Godbole, Lead Software Engineer with FactSet and Tarik Makota, AWS Principal Solutions Architect. In their own words “FactSet creates flexible, open data and software solutions […]
How to export an Amazon DynamoDB table to Amazon S3 using AWS Step Functions and AWS Glue
In this post, I show you how to use AWS Glue’s DynamoDB integration and AWS Step Functions to create a workflow to export your DynamoDB tables to S3 in Parquet. I also show how to create an Athena view for each table’s latest snapshot, giving you a consistent view of your DynamoDB table exports.