Say I have two machines with their own hardware and different specifications. They are PCs actually. The discussion here is if there is a way to put them online together such as their processing power could be balanced, like a cluster. Except, the cluster has a specific connection and the machines are homogeneous.

Is it possible to use both machines to process things like only one? Say we want to use the processor from PC1 to work with an Oracle database instance that is stored in PC2 hard disk. Would that be something like a IaaS?

  • You don't want to use a RDBMS with remote files, even if you could do that (e.g. with NFS). So the RDBMS server would run on PC2 (not PC1) Jul 11, 2017 at 15:40
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    "Cloud" is a marketing term, not a technical term. When marketing people talk about "the cloud", the technical term is usually "other people's servers".
    – Philipp
    Jul 11, 2017 at 16:00
  • @Philipp: but the defining feature of "cloud" computing is precisely how it is marketed. It is also sometimes called utility computing, because in cloud computing, computing resources are marketed similar to resources like water and electricity. Jul 11, 2017 at 20:57
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    I am very confused by your question. Are you asking about the definition of "cloud computing" or are you asking how to use two computers? Jul 11, 2017 at 21:10
  • @Philipp: Well, not always. At my workplace, "Cloud" means "our servers, other people's software."
    – Kevin
    Jul 12, 2017 at 4:32

1 Answer 1


Yes, you could do something like with a Beowulf Cluster, but I wouldn't recommend it.

Best practice today is to keep the computers as separate linux servers, install a scheduler like Apache Mesos or Kubernetes to pool the compute resources and run apps in docker containers. This will allow you to maximize the available resources of the hosts and leave the heavy lifting to the scheduler.

As far as databases go, you would need to use something like Oracle RAC in order to leverage multiple servers, but this is something different entirely from your example.

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