10 Big Data Startups You Shouldn't Overlook12:00 PM EST Thu. Feb. 28, 2013
Like any new trend in computing, big data is ushering in a whole new generation of companies vying for their place in the spotlight. At this week's big data-focused Strata event, taking place in the heart of California's Silicon Valley, many of those startups emerged from the woodworks, touting their latest and greatest innovations.
Here are 10 big data startups that stuck out in the crowd.
Monte Zweben, CEO
Some might argue that the dawn of big data marks the end of relational databases, as organizations flock to new, more flexible data sources -- such as NoSQL databases like MongoDB -- to ensure the scalability they need to run big data applications.
But, Splice Machine, a startup based in San Francisco, believes traditional SQL and big data can live together in harmony. The company's Hadoop-based Splice SQL Engine marries the best of both the SQL and NoSQL worlds, offering a massively scalable database without compromising things like secondary indexes, transactional integrity, and full SQL support the way it argues some NoSQL databases do.
Splice Machine's SQL Engine also prevents companies from needing to overhaul their BI landscape to dig into big data, eliminating the need to rewrite existing SQL-based tools.
Gad Bashvitz, Founder and CEO
Olset, a San Francisco-based startup that formed just four months ago, came to Strata to showcase how it uses big data to make things easier for frequent travelers.
Essentially a virtual travel agent, Olset fully automates the online travel booking process by knowing the preferences of its users. The system pulls in user information from sites ranging from Facebook to Expedia to get a sense of how its users like to travel, the types of hotels they prefer and more. From there, it suggests itineraries and makes bookings based entirely on those preferences. CEO Gad Bashvitz said users can even add in niche requirements, like a firm bed or a room far away from the elevator, and Olset will do the rest.
Kunal Agarwal and Shivnath Babu, Founders
Unravel isn't afraid to admit big data can be complicated. Founders Kunal Agarwal and Shivnath Babu (pictured) realize, for instance, how easy it is for organizations to get caught up trying to find the optimal configuration settings for Hadoop applications and wanted to do something to help.
So, in January they launched Unravel, a startup that provides optimization tools to help users spend less time worrying about their Hadoop infrastructures and focus instead on the true value of big data: making better business decisions.
Unravel does this through a series of visualization tools like Profiler, which maps out data flows and warns users when their configuration settings look off. Another tool, the What-If Engine, lets users see how the performance of their applications would be impacted if those configuration settings, or other parameters, are changed.
Ray Sikka, CEO
The point of leveraging big data analytics is ultimately to make better decisions. Sensitel, a big data startup based in Santa Clara, Calif., helps companies do just that.
By collecting data from tiny embedded sensors, the kind found in everything from smartphones to GPS devices, Sensitel's solutions allow companies to garner insights into parts of their business they rarely could before. Logistics service providers, for instance, use Sensitel's TrackAware solution to track over 100,000 shipments and ensure on-time delivery. Retail chains, meanwhile, leverage Sensitel's Staffcaster tool to identify which parts of their stores are most populated by shoppers (or at least their smartphones), and then direct their staff accordingly.
Sensitel was recently tapped to participate in SAP's Start-Up Focus Program, a program through which SAP helps to grow big data startups whose applications can work in conjunction with the SAP HANA in-memory database.
Carson Darling, Founder
Rest Devices drew a crowd at the big data Strata event this week, but not because of a flashy BI tool or a new Hadoop distribution like many of its peers. Its claim to fame? Pajamas.
Actually, babies' pajamas (or "onesies") to be exact. The Boston-based startup makes a line of onesies that come with tiny embedded sensors designed to track babies' breathing patterns while they sleep, and then transmit that data in real-time back to parents' mobile devices. It's a product that may mean not only the demise of the modern-day baby monitor, but a new way for doctors to monitor the health of their patients down the line.
James Ladd, Co-Founder and President
Vertascale came to Strata to show off SimpleSearch, its flagship product for performing quick and easy searches on big data.
Touted as being a "search engine for Hadoop," Vertascale's SimpleSearch tool provides indexing and real-time search capabilities for searching semi-structured or mix-structured data stores in Amazon S3 of the Hadoop File System (HDFS). But apart from providing business analysts with easy-to-use, self-service search capabilities, Vertascale said SimpleSearch also significantly speeds up Hadoop, a platform that hasn't always been praised for performance. According to the Menlo Park, Calif.-based startup, SimpleSearch can build a unique index that speeds up Hadoop queries by a factor of 1,000x.
Mara Lewis, Co-Founder and CEO
Stopped.at is a big data startup that melds analytics with social media to make your Web browsing experience just a little bit more rewarding.
Almost like Foursquare for the Web, Stopped.at lets users "check in" while visiting websites, earn points for doing so, and then redeem those points in their online stores to get rewards like store discounts, cash or iTunes gift cards. What's more, users can keep track of "trending websites" or sites their Facebook friends are visiting to keep tabs on the most popular online destinations.
Stopped.at also recommends new websites to users, based on the sites they already visit.
Chandra Shekhar Tekwani, CEO
Move over, Siri. There's a new personal assistant in town.
Its name is "Corey," and while it doesn't talk (at least not yet), it's poised to become executives' dream app for staying organized and never forgetting a contact. Developed by big data startup and SAP-backed Core Mobile Networks, Corey is a mobile app for iOS and Android that preps users for conference calls or meetings by pulling in relevant information about the person they're meeting with from social networking sites like LinkedIn.
This "smart, one touch assistant" also compiles information from Microsoft Outlook, various news sites and Salesforce.com on topics that are the most relevant to users before heading into a meeting. The app is targeted largely at the finance and healthcare industries.
Liz Derr, Founder and CEO
The ability to build more targeted, customized advertisements is one of big data's biggest value props. Simularity is putting itself out in front of that trend with its similarity analytics tools for big data environments.
Simularity's platform, which can perform both streaming and historical big data analysis, helps organizations find commonalities among massive unstructured data sets that can ultimately make them more competitive. Simularity in December signed on online book retailer Alibris, which uses Simularity to make product recommendations to customers based on the preferences of other shoppers with similar interests and buying patterns.
Simularity also has a Facebook app that offers users personalized recommendations based on the items they've "Liked."
Rick Dutta, CEO
Nexvisionix, also a member of SAP's big data-specific Start-Up Focus Program, provides big data analytics tools specifically for the retail space. But what makes the company unique -- and allows them to stand apart from the slew of other BI vendors targeting retailers today -- is that Nexvisionix doesn't assume all retail outlets are the same.
Instead, Nexvisionix splits its big data analytics tools into three distinct retail categories: softline (meaning clothes and linens), electronics and grocery. Within each of these categories, users will find analytics tools specific to merchandising, store operations, and CRM or promotion management, which unite to create a complete, end-to-end solution tailored to meet their retail needs -- not the store's down the street.