AWS Big Data Blog

Category: Amazon Redshift*

A Zero-Administration Amazon Redshift Database Loader

Ian Meyers is a Solutions Architecture Senior Manager with AWS With this new AWS Lambda function, it’s never been easier to get file data into Amazon Redshift. You simply push files into a variety of locations on Amazon S3 and have them automatically loaded into your Amazon Redshift clusters. Using AWS Lambda with Amazon Redshift […]

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Building Multi-AZ or Multi-Region Amazon Redshift Clusters

Erik Swensson is an AWS Solutions Architect. AWS Solutions Architect Patrick Shumate also contributed to this post. This post explores customer options for building multi-region or multi-availability zone (AZ) clusters. By default, Amazon Redshift has excellent tools to back up your cluster via snapshot to Amazon Simple Storage Service (Amazon S3). These snapshots can be […]

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Using Attunity CloudBeam at UMUC to Replicate Data to Amazon RDS and Amazon Redshift

Matt Yanchyshyn is a Principal Solutions Architect at AWS. Brad Helicher, Director of Cloud Business at Attunity, also contributed to this post. Attunity is an APN Big Data Competency Partner. Introduction University of Maryland University College’s mission is to provide a quality education at an affordable cost to busy professionals, mainly adults who are juggling […]

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Using Amazon Redshift to Analyze Your Elastic Load Balancer Traffic Logs

Biff Gaut is a Solutions Architect with AWS Introduction With the introduction of Elastic Load Balancing (ELB) access logs, administrators have a tremendous amount of data describing all traffic through their ELB. While Amazon Elastic MapReduce (Amazon EMR) and some partner tools are excellent solutions for ongoing, extensive analysis of this traffic, they can require […]

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Best Practices for Micro-Batch Loading on Amazon Redshift

Ian Meyers is a Solutions Architecture Senior Manager with AWS Data analysts always want the newest data in their data warehouse. Historically, when transaction-optimized databases were used for warehousing analysts would “trickle load” (replicate data from production systems into the data warehouse) at the expense of read throughput. Analytics data warehouses are traditionally loaded nightly […]

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