Database Reference
In-Depth Information
the proximity question will probably be an issue. Remember proximity is a
two-part measure:
• The distance to the system managing the data (i.e., the bandwidth
question)
• The distance to other enterprise data sources (i.e., the integrated
analysis dilemma)
The magnitude of this first element may be mitigated if the burden is only
endured for an initial or historic load. If the subsequent deltas are of a
manageable size, then the concerns may be significantly reduced. The
second element is a ratio. If there is little or no integrated analysis with
on-premise data sources, then the proximity issue is again less of a concern.
If there is a significant amount of integrated analysis, this may prove to be a
cloud deployment deal breaker.
On-premise deployments work well for the following:
• Custom deployments
• Data born on premise
• Secure data
An on-premise deployment is best suited for data that is born on premise
and that perhaps also needs to be integrated with other data sources that
may also reside locally. Having your own environment, although flexible, is
also a commitment of both compute and human resources. It therefore suits
predictable workloads, which can be more readily sized.
Summary
What have you learned? The world isn't quite what it once seemed. In the
time it has taken to move from SQL Server 2008 to SQL Server 2012 the
world has been turned upside down. Microsoft's data platform now includes
and embraces Linux deployments of open source technology running
Apache Hadoop. What's more, we have a variety of options available in
terms of our deployment choices. What we choose is largely down to
business need and data value (as it should be).
You should now understand the factors that could influence your
deployment choice and how to evaluate the options before you. You should
