AWS Big Data Blog
Category: Storage
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 […]
Nasdaq’s Architecture using Amazon EMR and Amazon S3 for Ad Hoc Access to a Massive Data Set
This is a guest post by Nate Sammons, a Principal Architect for Nasdaq The Nasdaq group of companies operates financial exchanges around the world and processes large volumes of data every day. We run a wide variety of analytic and surveillance systems, all of which require access to essentially the same data sets. The Nasdaq […]
Using AWS for Multi-instance, Multi-part Uploads
James Saull is a Principal Solutions Architect with AWS There are many advantages to using multi-part, multi-instance uploads for large files. First, the throughput is improved because you can upload parts in parallel. Amazon Simple Storage Service (Amazon S3) can store files up to 5TB, yet a single machine with a 1Gbps interface would take […]
Moving Big Data Into The Cloud with ExpeDat Gateway for Amazon S3
Matt Yanchyshyn is a Principal Solutions Architect with Amazon Web Services Introduction A previous blog post (Moving Big Data Into the Cloud with Tsunami UDP) discussed how Tsunami UDP is a fast and easy way to move large amounts of data to and from AWS. Specifically, we showed how you can use it to move […]
Moving Big Data into the Cloud with Tsunami UDP
Matt Yanchyshyn is a Principal Solutions Architect with Amazon Web Services AWS Solutions Architect Leo Zhadanovsky also contributed to this post. Introduction One of the biggest challenges facing companies that want to leverage the scale and elasticity of AWS for analytics is how to move their data into the cloud. It’s increasingly common to have […]