IBM DataWorks… the Next Big Data Thing
How vendors support open source technologies doesn’t follow a set path. Many start-ups and smaller companies (along with once-small, now-prosperous businesses) make near or complete commitments to open source for both philosophical and financial reasons. Many leverage Linux and other specific platforms at their developers’ or customers’ behest while others attempt to bend the technology to their own will or competitive advantage by creating proprietary forks.
That’s a critical issue because of the natural ways in which open source development evolves along with and very often leads innovative industry trends. For example, the big data technologies and initiatives roiling IT over the past half-decade have been driven by open source Apache Software Foundation projects, including Hadoop, MapReduce and Spark. In fact, vendors that ignore or fail to support these products find themselves falling quickly behind the curve technologically and competitively.
IBM has pursued a singular path in its own open source efforts. In the late 1990s, the company committed $1B to develop Linux solutions for its z Systems mainframes and other server platforms. That was followed by substantial investments in a range of platform and community-building projects, along with open sourcing technologies the company developed in-house with Eclipse and the POWER chip architecture among the most notable of these.
The company also proactively invested in Apache Spark and other complementary advanced analytics and big data projects. What does any of this have to do with anything? IBM’s newly announced Project DataWorks qualifies as both the culmination of and a natural next step for the company’s open source big data strategies and goals. As such, it’s worth close consideration.
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NOTE: This column was originally published in the Pund-IT Review.