We believe multitenancy creates cost advantages for ISVs like HarrisData, and intend to leverage multitenancy in whatever forms provide the most value to our customers. However, a religious commitment to multitenancy ahead of real customer requirements is just pandering to investors.
Multitenancy is a buzzword getting a lot of attention these days. Over at ZDNet, Eric Lai started quite a conversation looking at what he felt were Four Big Problems with Multitenancy from an enterprise application space. Frank Scavo replied that the post was a Mischaracterization of Multitenancy in his blog.
Multitenancy is an interesting word. You won’t find it in a dictionary (unless you use Wikipedia’s definition as your dictionary – and even that definition is still considered suspect by the Wikipedia editors almost two years after first appearing). It’s a word that conveys an obvious meaning on a vendor’s or expert’s slide, and probably shouldn’t need a strict definition. But we’re in the technology business, and folks like to debate what words mean. Even the National Institute of Standards and Technology (NIST) definition of cloud computing contains only one reference to ‘multi-tenant’, and it’s only used in the definition of the term ‘resource pooling’. Multi-tenancy and cloud computing looks at the definition of multi-tenant by starting with the definition of a tenant – in which there is some ambiguity. Let’s ignore the strict definition of the word multi-tenant and use a more pragmatic definition. A multitenant solution allows two tenants to share resources with the express desire to lower cost.
With that background, here’s three things to ponder when considering the next claim that a product is or isn’t great because it is multitenant:
Our take: We believe multitenancy creates cost advantages for ISVs like HarrisData, and intend to leverage multitenancy in whatever forms provide the most value to our customers. However, a religious commitment to multitenancy ahead of real customer requirements is just pandering to investors.
Written by Lane Nelson, “…for the first time in close to a century it’s probably easier to make a fortune in auto manufacturing working with (or founding) a startup than by signing-on with one of the big companies.”
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Written by Lane Nelson Using a machine learning solution allows the ERP to imitate the manager’s decision criteria, and then allows the managers to focus on approving those decisions and managing the exceptions.
A recent article from Joshua Greenbaum at EAC reignited passion around the topic of enterprise software implementations and the implications it has on companies and their employee’s livelihood.
HarrisData has been an IBM business partner for decades.