AWS Big Data Blog

Category: Database

Migrating Metadata when Encrypting an Amazon Redshift Cluster

NOTE: Amazon Redshift now supports enabling and disabling encryption with 1-click. For more information, please review this “What’s New” post. ————————————— John Loughlin is a Solutions Architect with Amazon Web Services. A customer came to us asking for help expanding and modifying their Amazon Redshift cluster. In the course of responding to their request, we […]

Scaling Writes on Amazon DynamoDB Tables with Global Secondary Indexes

Ian Meyers is a Solutions Architecture Senior Manager with AWS Amazon DynamoDB is a fast, flexible, and fully managed NoSQL database service that supports both document and key-value store models that need consistent, single-digit millisecond latency at any scale. In this post, we discuss a technique that can be used with DynamoDB to ensure virtually […]

Introduction to Python UDFs in Amazon Redshift

Christopher Crosbie is a Healthcare and Life Science Solutions Architect with Amazon Web Services When your doctor takes out a prescription pad at your yearly checkup, do you ever stop to wonder what goes into her thought process as she decides on which drug to scribble down? We assume that journals of scientific evidence coupled […]

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 […]

Building and Maintaining an Amazon S3 Metadata Index without Servers

Mike Deck is a Solutions Architect with AWS Amazon S3 is a simple key-based object store whose scalability and low cost make it ideal for storing large datasets. Its design enables S3 to provide excellent performance for storing and retrieving objects based on a known key. Finding objects based on other attributes, however, requires doing […]

Connecting R with Amazon Redshift

Markus Schmidberger is a Senior Big Data Consultant for AWS Professional Services Amazon Redshift is a fast, petabyte-scale cloud data warehouse for PB of data. AWS customers are moving huge amounts of structured data into Amazon Redshift to offload analytics workloads or to operate their DWH fully in the cloud. Business intelligence and analytic teams […]

Presto-Amazon Kinesis Connector for Interactively Querying Streaming Data

This is a guest post by Sivaramakrishnan Narayanan, Member of Technical Staff at Qubole, and Xing Quan, Director of Product Management at Qubole. Qubole is an AWS Advanced Technology Partner. Amazon Kinesis is a scalable and fully managed service for streaming large, distributed data sets. As applications (particularly on mobile and wearable devices) start to […]

How Expedia Implemented Near Real-time Analysis of Interdependent Datasets

This is a guest post by Stephen Verstraete, a manager at Pariveda Solutions. Pariveda Solutions is an AWS Premier Consulting Partner. Common patterns exist for batch processing and real-time processing of Big Data. However, we haven’t seen patterns that allow us to process batches of dependent data in real-time. Expedia’s marketing group needed to analyze […]

Building a Binary Classification Model with Amazon Machine Learning and Amazon Redshift

Guy Ernest is a Solutions Architect with AWS This post builds on Guy’s earlier posts Building a Numeric Regression Model with Amazon Machine Learning and Building a Multi-Class ML Model with Amazon Machine Learning. Many decisions in life are binary, answered either Yes or No. Many business problems also have binary answers. For example: “Is […]