IBM Systems Magazine, Power Systems - October 2017 - 25
has its differences. If it's the same
database that's used elsewhere,
it's a benefit. If your support staff
can use the same database for
multiple workloads, that's ideal,
Data center support staff may
have to learn the new models,
paradigms and APIs for accessing
that database. Performance,
performance tuning, methods
for configuring your data and
your data ingest will be different
from traditional databases.
Some OSDBs may be simpler
than traditional ones because
they're fit-for-purpose, i.e., they
have a predefined document that
describes what's needed. While
the learning curve probably isn't
as high as it is with pre-existing
proprietary databases, OSDBs will
be new to many people.
If you're using new OSDBs,
the data center must work with
the open-source community.
"Many data centers benefit
from the responsiveness of the
community and collaboration
with developers who are trying
to solve the same problems you
are," Huizenga says.
Because basic versions of OSDBs
are typically free, companies may
believe they're the lowest cost
solution. However, organizations
must examine a variety of factors
to determine cost. Those factors
include incidental costs, support
model costs, performancetuning expenses and impact on
your database administrators
Most relational databases are stored on a
single server. When more database performance is required, the server is scaled
up by the addition of more resources.
Relational databases don't have built-in
features to spread data across more than
one server to take advantage of additional
processing power. In contrast, NoSQL
databases can scale horizontally, or "scale
out," by adding more servers.
Sharding is a way to divide data
across a cluster so it can be processed in
parallel. Many NoSQL solutions support
auto-sharding, where data is automatically spread across multiple servers with
applications requiring no knowledge of
the cluster. Data and queries are automatically balanced across the servers.
Auto-sharding is commonly used with
NoSQL deployments in a cloud.
ibmsystemsmag.com OCTOBER 2017 // 25