AWS Big Data Blog
Category: HAQM Kinesis
Writing SQL on Streaming Data with HAQM Kinesis Analytics – Part 1
This post introduces you to HAQM Kinesis Analytics, the fundamentals of writing ANSI-Standard SQL over streaming data, and works through a simple example application that continuously generates metrics over time windows.
Process Large DynamoDB Streams Using Multiple HAQM Kinesis Client Library (KCL) Workers
Asmita Barve-Karandikar is an SDE with DynamoDB Introduction Imagine you own a popular mobile health app, with millions of users worldwide, that continuously records new information. It sends over one million updates per second to its master data store and needs the updates to be relayed to various replicas across different regions in real time. […]
How SmartNews Built a Lambda Architecture on AWS to Analyze Customer Behavior and Recommend Content
This is a guest post by Takumi Sakamoto, a software engineer at SmartNews. SmartNews in their own words: “SmartNews is a machine learning-based news discovery app that delivers the very best stories on the Web for more than 18 million users worldwide.” Data processing is one of the key technologies for SmartNews. Every team’s workload […]
Analyze Realtime Data from HAQM Kinesis Streams Using Zeppelin and Spark Streaming
This post shows you how you can use Spark Streaming to process data coming from HAQM Kinesis streams, build some graphs using Zeppelin, and then store the Zeppelin notebook in HAQM S3.
Processing HAQM DynamoDB Streams Using the HAQM Kinesis Client Library
Asmita Barve-Karandikar is an SDE with DynamoDB Customers often want to process streams on an HAQM DynamoDB table with a significant number of partitions or with a high throughput. AWS Lambda and the DynamoDB Streams Kinesis Adapter are two ways to consume DynamoDB streams in a scalable way. While Lambda lets you run your application […]
Real-time in-memory OLTP and Analytics with Apache Ignite on AWS
February 9, 2024: HAQM Kinesis Data Firehose has been renamed to HAQM Data Firehose. Read the AWS What’s New post to learn more. Babu Elumalai is a Solutions Architect with AWS Organizations are generating tremendous amounts of data, and they increasingly need tools and systems that help them use this data to make decisions. The […]
Analyze a Time Series in Real Time with AWS Lambda, HAQM Kinesis and HAQM DynamoDB Streams
This is a guest post by Richard Freeman, Ph.D., a solutions architect and data scientist at JustGiving. JustGiving in their own words: “We are one of the world’s largest social platforms for giving that’s helped 26.1 million registered users in 196 countries raise $3.8 billion for over 27,000 good causes.” Introduction As more devices, sensors […]
Optimize Spark-Streaming to Efficiently Process HAQM Kinesis Streams
Rahul Bhartia is a Solutions Architect with AWS Martin Schade, a Solutions Architect with AWS, also contributed to this post. Do you use real-time analytics on AWS to quickly extract value from large volumes of data streams? For example, have you built a recommendation engine on clickstream data to personalize content suggestions in real time […]
Process HAQM Kinesis Aggregated Data with AWS Lambda
Ian Meyers is a Solutions Architecture Senior Manager with AWS Last year, we introduced the HAQM Kinesis Producer Library (KPL) to simplify the development of applications that need to send data to HAQM Kinesis Streams. Many customers use aggregation, which allows you to send multiple records to a single HAQM Kinesis Streams record. Although the […]
Querying HAQM Kinesis Streams Directly with SQL and Spark Streaming
Amo Abeyaratne is a Big Data consultant with AWS Professional Services Introduction What if you could use your SQL knowledge to discover patterns directly from an incoming stream of data? Streaming analytics is a very popular topic of conversation around big data use cases. These use cases can vary from just accumulating simple web transaction […]