IBM Systems Magazine, Power Systems - October 2017 - 23
ata is critical for business
companies are demanding
faster access to analytics that rely
on data coming from all kinds of
sources containing structured and
unstructured data. Databases and
database technologies are evolving
to better serve these needs. While
traditional relational databases
remain well-used tools for
analysis, open-source databases
(OSDBs) that can easily handle
unstructured data are becoming
essential for most businesses.
Relational databases use
the relational model of tables,
columns and rows to store data.
SQL and stored procedures
are used to query the data.
Traditional relational databases
are developed, maintained and
supported by an ISV or similar
software development companies.
Relational databases continue
to be an excellent way to store
transactional and structured data.
However, enterprises must process
growing amounts of diverse data,
which requires different sorts of
The traditional database
architecture is hitting limits
PHOTO ILLUSTRATION BY GETTY / PHIL LEO / MICHAEL DENORA
in performance, causing enterprises to examine
alternatives. "Traditional databases were not
designed to cope with the scale and agile demands
required by modern applications; nor were they
created to leverage storage and processing power
that are readily available today," says Beth L.
Hoffman, IBM executive IT specialist and big data
and analytics ISV solution architect.
OSDBs, which have existed for a while, provide
broader capabilities. Some support the traditional
relational database model, while others support data
using approaches beyond SQL-like query languages.
For instance, NoSQL databases have dynamic
schemas that provide more flexibility.
The proliferation of data types is driving the move
to OSDBs, says Gerrit Huizenga, STSM, Power*
open-source ecosystem lead. The standard Oracle or
Microsoft* SQL server is focused on the relationship
Organizations want to harness
unstructured data, using it to inform
Open-source databases can help
organizations mine unstructured data
Solutions such as Hadoop and Spark
provide enterprises with the flexibility to
dynamically grow and shrink environments
as the data size changes.
between defined data fields, which
works well for some workloads.
However, analytic workloads,
which are a predecessor to
cognitive and big data, require
databases that operate differently
and can yield effective answers
or insights quickly. OSDB models
include everything from key
value databases to content store
databases to multivalue databases
that focus on multidimensional
or freeform search. "Traditional
database development isn't
necessarily as nimble as open
source," he explains.
The Linux Connection
The demand for open source
and the Linux* OS is another
reason organizations are
employing OSDBs. Unlike their
proprietary comrades, the source
code for OSDBs is publicly
available and customizable. The
OSDB model relies on community
support, which means you may
get better response for less cost,
Most OSDBs are supported
on the Linux OS, which means
enterprises that already use it can
leverage their existing IT staff
ibmsystemsmag.com OCTOBER 2017 // 23