AWS Big Data Blog
Category: Amazon Kinesis
Validate, evolve, and control schemas in Amazon MSK and Amazon Kinesis Data Streams with AWS Glue Schema Registry
Data streaming technologies like Apache Kafka and Amazon Kinesis Data Streams capture and distribute data generated by thousands or millions of applications, websites, or machines. These technologies serve as a highly available transport layer that decouples the data-producing applications from data processors. However, the sheer number of applications producing, processing, routing, and consuming data can […]
Read MoreBuilding a real-time notification system with Amazon Kinesis Data Streams for Amazon DynamoDB and Amazon Kinesis Data Analytics for Apache Flink
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 insights on sensor activity across various industries, including smart spaces, connected factories, smart packing, fitness monitoring, and more. It’s important to store these data points in a centralized […]
Read MoreBuilding an ad-to-order conversion engine with Amazon Kinesis, AWS Glue, and Amazon QuickSight
Businesses in ecommerce have the challenge of measuring their ad-to-order conversion ratio for ads or promotional campaigns displayed on a webpage. Tracking the number of users that clicked on a particular promotional ad and the number of users who actually added items to their cart or placed an order helps measure the ad’s effectiveness. Utilizing […]
Read MoreBuilding a scalable streaming data processor with Amazon Kinesis Data Streams on AWS Fargate
Data is ubiquitous in businesses today, and the volume and speed of incoming data are constantly increasing. To derive insights from data, it’s essential to deliver it to a data lake or a data store and analyze it. Real-time or near-real-time data delivery can be cost prohibitive, therefore an efficient architecture is key for processing, […]
Read MoreBest practices for consuming Amazon Kinesis Data Streams using AWS Lambda
Many organizations are processing and analyzing clickstream data in real time from customer-facing applications to look for new business opportunities and identify security incidents in real time. A common practice is to consolidate and enrich logs from applications and servers in real time to proactively identify and resolve failure scenarios and significantly reduce application downtime. […]
Read MoreDetect 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 […]
Read MoreMigrating from Vertica to Amazon Redshift
Amazon Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. With Amazon Redshift, you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. When you use Vertica, you have to install and upgrade Vertica database software and manage the […]
Read MoreUnified serverless streaming ETL architecture with Amazon Kinesis Data Analytics
Businesses across the world are seeing a massive influx of data at an enormous pace through multiple channels. With the advent of cloud computing, many companies are realizing the benefits of getting their data into the cloud to gain meaningful insights and save costs on data processing and storage. As businesses embark on their journey […]
Read MoreStreaming data from Amazon S3 to Amazon Kinesis Data Streams using AWS DMS
Stream processing is very useful in use cases where we need to detect a problem quickly and improve the outcome based on data, for example production line monitoring or supply chain optimizations. This blog post walks you through process of streaming existing data files and ongoing changes from Amazon Simple Storage Service (Amazon S3) to […]
Read MoreEnhanced monitoring and automatic scaling for Apache Flink
Thousands of developers use Apache Flink to build streaming applications to transform and analyze data in real time. Apache Flink is an open-source framework and engine for processing data streams. It’s highly available and scalable, delivering high throughput and low latency for the most demanding stream-processing applications. Monitoring and scaling your applications is critical to […]
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