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Summary:

Rather than bombard readers with information with the holidays officially upon us, I’m interested to hear your thoughts. Which of the following big data approaches and startups will thrive, which will remain relegated to specific use cases, and which will simply fade into oblivion?

survival of the fittest

Since its inception, GigaOM has covered the advent of the big data era, where the web, sensors, devices and servers combine to bury organizations in data. Over the past couple of years — more so over the past year — there has been a seeming exponential increase in tools designed to help organizations harness this data, to not only house, but also to derive meaningful insights from it. It stands to reason, however, that not every approach and vendor will thrive, or even survive.

Rather than bombard readers with information with the holidays officially upon us, I’m interested to hear your thoughts. Which of the following approaches and startups (or others not listed) will thrive and become part of mainstream IT going forward, which will remain relegated to R&D departments and large web companies, and which will simply fade into oblivion? I’ll go out on a limb and predict that Hadoop is here to stay — what do you think?

Image courtesy of Flickr user somegeekintn.

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  1. Hadoop will probably stay until next generation distributed data processing platform becomes mature enough. Google has already published some details on Dremel and some other in-house technologies which will catch up in a open source world sooner or later (rather sooner than later).

    All M/R like tools are niche technologies and will never become mainstream (especially when some of them are not free).

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