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Provision cloud Hadoop, Spark, R Server, HBase, and Storm clusters

  • Pros

  • Open source big data
  • Legacy workloads
  • Existing Hadoop skills
  • Managed service
  • Portability between clouds and on-prem
  • Data Factory integration
  • Flexible compute options (VMs)
  • Customizable clusters
  • Cons

  • Decline in Hadoop adoption
  • Relatively high operational / admin costs
  • Steep learning curve
  • No consumption-based SKUs

Read our blog posts about HDInsight

AWS vs Azure vs Google Cloud Platform - Analytics & Big Data

AWS vs Azure vs Google Cloud Platform - Analytics & Big Data

Jess Panni

Embracing Disruption - Financial Services and the Microsoft Cloud

Embracing Disruption - Financial Services and the Microsoft Cloud

Howard van Rooijen

We have produced an insightful booklet called "Embracing Disruption - Financial Services and the Microsoft Cloud" which examines the challenges and opportunities for the Financial Service Industry in the UK, through the lens of Microsoft Azure, Security, Privacy & Data Sovereignty, Data Ingestion, Transformation & Enrichment, Big Compute, Big Data, Insights & Visualisation, Infrastructure, Ops & Support, and the API Economy.
Spinning up 16,000 A1 Virtual Machines on Azure Batch

Spinning up 16,000 A1 Virtual Machines on Azure Batch

Howard van Rooijen

We recently completed a technical proof of concept to see if the new Azure Batch service could scale to meet the demands of a Big Compute workload.