AWS Big Data Blog

Category: Amazon Kinesis

Processing Amazon DynamoDB Streams Using the Amazon Kinesis Client Library

Asmita Barve-Karandikar is an SDE with DynamoDB Customers often want to process streams on an Amazon 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 […]

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Real-time in-memory OLTP and Analytics with Apache Ignite on AWS

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 data has both immediate value (for example, trying to understand how a new promotion is performing in real time) and historic value (trying […]

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Analyze a Time Series in Real Time with AWS Lambda, Amazon Kinesis and Amazon 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 […]

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Optimize Spark-Streaming to Efficiently Process Amazon 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 […]

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Process Amazon Kinesis Aggregated Data with AWS Lambda

Ian Meyers is a Solutions Architecture Senior Manager with AWS Last year, we introduced the Amazon Kinesis Producer Library (KPL) to simplify the development of applications that need to send data to Amazon Kinesis Streams. Many customers use aggregation, which allows you to send multiple records to a single Amazon Kinesis Streams record.  Although the […]

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Querying Amazon 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 […]

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Building a Near Real-Time Discovery Platform with AWS

Assaf Mentzer is a Senior Consultant for AWS Professional Services In the spirit of the U.S presidential election of 2016, in this post I use Twitter public streams to analyze the candidates’ performance, both Republican and Democrat, in a near real-time fashion. I show you how to integrate AWS managed services—Amazon Kinesis Firehose, AWS Lambda […]

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Integrating Splunk with Amazon Kinesis Streams

Prahlad Rao is a Solutions Architect wih AWS It is important to not only be able to stream and ingest terabytes of data at scale, but to quickly get insights and visualize data using available tools and technologies. The Amazon Kinesis platform of managed services enables continuous capture and stores terabytes of data per hour from […]

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Persist Streaming Data to Amazon S3 using Amazon Kinesis Firehose and AWS Lambda

Derek Graeber is a Senior Consultant in Big Data Analytics for AWS Professional Services Streaming data analytics is becoming main-stream (pun intended) in large enterprises as the technology stacks have become more user-friendly to implement. For example, Spark-Streaming connected to an Amazon Kinesis stream is a typical model for real-time analytics. But one area that […]

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