Principled Technologies Big Data Workloads Challenge: AWS vs. IBM Cloud (IGC)

Provided by: IBM
Topic: Data Management
Format: HTML
Faster big data analytics and better responsiveness with IBM Cloud

An IBM Cloud configuration completed a big data analytics workload in less time and with greater throughput than an AWS solution

The cloud offers elasticity and fexibility to meet a range of demands for big data initiatives. Not all infrastructure-as-a-service (IaaS) providers are the same, though, and your organization requires performance and speed advantages to make big data initiatives successful.

At Principled Technologies, we ran a Hadoop-based big data workload and a series of networking tests on two IaaS providers: IBM® Cloud and Amazon® Web Services (AWS®) Elastic Compute Cloud® (EC2®). The IBM Cloud solution clustered data points on virtual machines (VMs) faster and had higher throughput while working with big data than the AWS solution did. Compared to AWS, an IBM Cloud solution offers shorter wait times for the big data analytics that will drive your next marketing campaign, app, or operational improvements.

The IBM Cloud solution transferred data and sent pings between data centers in less time, too. Faster data delivery to and from data centers in the United States (US), United Kingdom (UK), and Japan means your global workforce could communicate, plan, and collaborate faster.

Your organization’s IaaS provider affects your big data initiatives and trans-global communication. When it comes to performance and speed for big data, our findings show that an IBM Cloud solution can benefit your organization more than an AWS solution.

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