The Big Data market is heating up, and unlike some overhyped trends (social media), it’s pretty easy to pinpoint ROI with these tools.
When we put out calls for nominees through the Story Source Newsletter, HARO, Twitter, and other channels, we received more than 100 recommendations. Usually, when we get that many, a good chunk of them can be dismissed out of hand. Some are clearly science projects; others have zero funding, no management pedigree and a dubious value proposition, while a few are clearly the product of malarial hallucinations.
Not so this time. Very few of the startups we looked at were whacky long shots. Most were decent ideas, backed by real VC money and seasoned management teams.
Recently, we’ve changed how the final 10 startups to watch are selected. First, a big list of nominees on Startup50.com are compiled. (Check out the Big Data list of 42 nominees here.) Then, we let readers vote on their favorites.
This time around another wrinkle was introduced. Startups left off the big list can challenge specific startups on it, trying to steal their spot away. If the challenge is deemed to have merit, we’ll set up a separate vote. Sqrrl and DataStax both fought their way onto the list of nominees through challenges.
All told, more than 11,000 people voted for their favorite Big Data startups, with Cloudant winning, SiSense coming in a close second and SumAll finishing a strong third.
This time around we weighed voting more heavily than normal. Usually, voting is given a weight of about 30 percent, and then we turn to other factors, such as funding, the pedigree of the management team and the viability of the startup’s roadmap.
However, the entire list of 42 Big Data nominees (plus several others that initially escaped our notice) is ridiculously strong.
Take Xplenty, for instance. They finished eighth in voting, but we considered bumping them because the startup is only a year old, hasn’t raised significant funding and doesn’t yet have big-name customers. All marks against it.
Balancing those negatives is the fact that voting does matter, and roundups like this are best if they include a mix of top startups well on the way to reaching their potential along with some startups that are pretty much all potential right now.
As we started looking at potential replacements, we realized that any of the top 25 or so vote-getters could make solid arguments for inclusion.
Frankly, we could have slotted Platfora, Cloudmeter, CloudPhysics, Sqrrl, RainStor, Rocket Fuel or several others in Xplenty’s place. Big Data startups, unlike some other spaces, have real substance to them. They are building viable products that target real-world pain points (pain points businesses are willing to pay to solve–today), and most Big Data startups are well-funded with solid management teams. It is just a really strong space.
So, Xplenty stuck. Yes, they’re more raw potential than giant killer at this stage, but their coding-free Hadoop Big Data service is simple, easy to use and affordable for even the mid-market.