The two largest providers of public cloud services at this point are clearly Amazon Web Services (AWS) and Microsoft Azure. Now those two cloud services can share access to a common Big Data platform.
Hortonworks today announced that Hortonworks Data Cloud (HDC) is now available on AWS. Previously, HDC, which combines Hadoop and the Apache Spark in-memory computing framework into a single offering, has only been available on Azure as part of an alliance between Hortonworks and Azure.https://o1.qnsr.com/log/p.gif?;n=203;c=204663295;s=11915;x=7936;f=201904081034270;u=j;z=TIMESTAMP;a=20410779;e=iShaun Connolly, chief strategy officer at Hortonworks, says IT organizations will now be able to evaluate both Azure and AWS on a per Big Data application workload basis with an eye toward creating an integrated multi-cloud environment spanning multiple Big Data applications. In both cases, Connolly notes that IT organizations can pay to use HDC on a monthly or yearly subscription basis.
As AWS and Azure continue to increase in size, IT organizations also need to be aware of the impact data gravity will start to have on their cloud platform decisions. As the amount of data available on a specific cloud platform increases, it starts to create a level of pull that becomes difficult to ignore. Rather than trying to pull data in and out of that cloud, it becomes more cost-effective to host applications wherever the largest amount of data resides. Most IT organizations today have most of their data still running on-premises. Because of that issue, Connolly says Hortonworks envisions organizations opting to deploy HCP on-premises and in the cloud to create a hybrid environment.
“We think it’s going to be all about having connected data,” says Connolly.
It’s unclear to what degree IT organizations will be able to play AWS off against Azure to force them to bid for specific application workloads. But when it comes to IT, history has shown time and again that having choice usually results in more economic leverage for the end customer.