AWS Big Data Blog
Tag: Amazon Kinesis
Analyze Realtime Data from Amazon Kinesis Streams Using Zeppelin and Spark Streaming
This post shows you how you can use Spark Streaming to process data coming from Amazon Kinesis streams, build some graphs using Zeppelin, and then store the Zeppelin notebook in Amazon S3.
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 […]
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 […]
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 […]
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 […]
Building a Near Real-Time Discovery Platform with AWS
September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Assaf Mentzer is a Senior Consultant for AWS Professional Services In the spirit of the U.S presidential […]
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 […]
Persist Streaming Data to Amazon S3 using Amazon Data Firehose and AWS Lambda
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. 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 […]
Integrating Amazon Kinesis, Amazon S3 and Amazon Redshift with Cascading on Amazon EMR
This is a guest post by Ryan Desmond, Solutions Architect at Concurrent. Concurrent is an AWS Advanced Technology Partner. With Amazon Kinesis developers can quickly store, collate and access large, distributed data streams such as access logs, click streams and IoT data in real-time. The question then becomes, how can we access and leverage this […]
Implementing Efficient and Reliable Producers with the Amazon Kinesis Producer Library
Kevin Deng is an SDE with the Amazon Kinesis team and is the lead author of the Amazon Kinesis Producer Library How do you vertically scale an Amazon Kinesis producer application by 100x? While it’s easy to get started with streaming data into Amazon Kinesis, streaming large volumes of data efficiently and reliably presents some […]