10 hot big data startups to watch

Big data startups are building viable products that target real-world problems, and most are well-funded with solid management teams. Here are 10 to watch

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Why they're on this list: ScaleArc finished sixth in Startup50.com voting. They've raised serious VC money and have a long string of customer wins.

At Interop last month Singh pointed out that the growth of online and mobile applications is straining traditional database infrastructures. For companies doing business online, application availability and performance are key determinants of the customer experience and, ultimately, revenue.

However, companies struggle with the complex challenge of growing their database infrastructures to handle increasing demand, without negatively impacting the customer experience, or consuming resources that may be better used elsewhere. Traditional SQL environments are bogged down by an increasing volume of database queries from a growing number of applications that need access to structured data  -- leading to poor application performance and system outages.

And the problem is even worse for mobile applications, as performance takes an even bigger hit with increased latency.

Singh argues that companies need a way to optimize SQL query traffic without extensive modifications to existing applications or databases. To improve performance, they need to offload existing databases without investing in costly new infrastructure. Finally, they need full visibility into SQL traffic to more efficiently troubleshoot and resolve issues before they become major problems that impact revenue.

ScaleArc's flagship product, iDB, is software that inserts transparently between applications and databases, requiring no modifications to applications or databases. ScaleArc claims that it can be deployed in about 15 minutes. Then, users gain visibility into all database traffic with granular real-time SQL analytics.

iDB provides instant scalability and higher availability for databases with dynamic clustering, load balancing and sharding capabilities, and it provides a transparent SQL-NoSQL hybrid caching engine, which lets any application use a NoSQL cache without any code changes or drivers.

Market potential and competitive landscape: ScaleArc estimates that this market space is worth more than $2 billion (they're far more conservative than most analysts).

Competitors include ScaleBase and ParElastic.

Existing customers include Demand Media, Disney UTV, KIXEYE, Sazze (dealspl.us), Flipkart, Weather Decision Technologies and others.

7. SiSense

What they do: Provide big data analytics platforms.

Headquarters: Redwood City, Calif., with an R&D Center in Tel Aviv, Israel

CEO: Amit Bendov. He was formerly CMO of Panaya and SVP of Worldwide Marketing at ClickSoftware.

Founded: 2010 (they were technically founded in 2004, but were really just a side project for the five founders until 2010, and their official launch was 2012)

Funding: In April, SiSense closed a $10 million Series B round of funding led by Battery Ventures with participation from Opus Capital and Genesis Partners. A $4 million Series A round was secured in 2010.

Why they're on this list: SiSense finished second in Startup50.com voting, has solid VC backing and a good-sized list of customers.

According to SiSense, traditional big data analytics solutions are like battleships: They're expensive, complicated to operate, and are actually overkill for most businesses, which just don't need that much processing. The typical business does not need to analyze petabytes of data. Rather, they'd be happy gaining insights on terabytes of data, but that's either too expensive or forces them to rely on in-memory solutions, which cannot later scale to handle massive amounts of data.

SiSense Prism is built to offer big data analytics technology to businesses of all sizes. With no coding or scripting required, business analysts can analyze data themselves, without having to draw IT or data scientists into the process. SiSense claims that Prism allows non-technical users to analyze 100 times more data than current in-memory analytics solutions, and it does so 10 times faster. There's no need to set up complex data warehouse systems or OLAP cubes.

Prism is powered by SiSense's Elasticube technology, which features a columnar data store, strong data compression, parallel processing, and advanced query optimization to offer analytical processing power previously available only with high-end solutions.

Market potential and competitive landscape: Wikibon believes the big data market will exceed $47 billion by 2017. SiSense competitors include Tableau, QlikView and SAP HANA.

Customers include NASA, ESPN, Target, eBay, fiverr, Online Commerce Group, Plastic Jungle, and Magellan Vacations.

8. Skytree

What they do: Develop machine-learning-based platforms for big data analytics.

Headquarters: San Jose, Calif.

CEO: Martin Hack, who previously served as a director of marketing for GreenBorder Technologies (acquired by Google) and as a product line manager for SonicWall.

Founded: 2012

Funding: Skytree just secured (April 2013) $18 million in Series A funding. U.S. Venture Partners led the round and was joined by a new investor syndicate that includes UPS and Scott McNealy, co-founder and former CEO of Sun and Chairman of Wayin. Additional investors include Javelin Venture Partners and Osage University Partners. To date, Skytree has raised a total of $19.6 million.

Why they're on this list: Skytree finished in the top 10 in Startup50.com voting and has already lined up big-name customers.

According to Skytree, advanced analytics, contrary to popular belief, "is not a meat grinder into which you can dump data in one end and expect nuggets of wisdom to come out of the other end."

Skytree has created a general purpose platform that allows data scientists to focus on what matters most, which Skytree says is Mean Time to Insights (MTI), and focus on what they are good at: building and deploying analytic models rather than coding algorithms. Skytree is delivered as an application within a data center that can be used by many, as opposed to the traditional delivery model: an individual application used on a single PC.

[ Why Your IT Department Needs Data Scientists ]
[ What it Takes to Be a Data Scientist ]

Skytree argues that machine learning is the key that unlocks an entire treasure trove of predictions, customer recommendations, and anomaly detections that most people don't even know are possible. Machine learning solves that problem by unleashing algorithms on massive amounts of data and finding patterns that data scientists didn't even know existed.

Competitive landscape: Skytree says that most of the competition they run into is either from roll-your-own solutions or from legacy BI platforms from the likes of SAS and IBM, which potential customers may simply choose to stick with.

Customers include eHarmony, SETI, USGA, and Adconion Media.

9. SumAll

What they do: Provide data analytics tools focused on delivering marketing, sales and social media insights.

Headquarters: New York

CEO: Dane Atkinson. He was formerly CEO of Squarespace.

Founded: 2011

Funding: SumAll is backed by two rounds of funding that total $7.5 million from Battery Ventures, Wellington Partners, Matrix and General Catalyst.

Why they're on this list: SumAll finished third in Startup50.com voting, and CEO Dane Atkinson has seen several startups through to successful exits.

SumAll's product is an analytics tool that helps businesses make more money by using their own data. SumAll tries to break down various data silos, from those associated with legacy apps to those involved with social media.

SumAll brings all the disparate revenue, payment, social and organic traffic data into one place so users can see the interactions across their business and understand if a social campaign is driving traffic which is converting into traffic. SumAll can help businesses figure out, say, the value of a "like" on Facebook or the value of a website visit.

Competitive landscape: These aren't necessarily head-to-head comparisons, but SumAll will compete with Hootsuite, Nimble, Gooddata and Kissmetrics.

Customers include Siemens, Diamond Candles, and Urbio.

10. Xplenty

What they do: Provide Hadoop as a Service for big data analytics.

Headquarters: Tel Aviv, Israel

CEO: Yaniv Mor. Prior to founding Xplenty, Mor managed the NSW SQL Services practice at Red Rock Consulting.

Founded: 2012

Funding: They're backed by an undisclosed amount of seed funding raised from Magma Venture Capital in June 2012.

Why they're on this list: Hadoop is being hyped to the moon these days, but development, implementation and maintenance of Hadoop require a very specific and arcane skill set. Xplenty's goal is to eliminate your need to learn any of that.

Xplenty provides a data integration platform that processes big data. A drag-and-drop interface eliminates the need to write complex scripts or code of any kind.

Xplenty is cloud based, so there is no installation of anything on an end user's servers, and there is no software to download onto workstations. With automated server configuration, users simply point to a data source, configure the data transformation tasks and tell the platform where to right the results to. Xplenty's platform uses SQL terminology, so for data analysts, the learning curve should be minimal.

Market potential and competitive landscape: According to TechNavio, the Hadoop-as-a-Service market will top $19 billion by 2016. Xplenty's main competitor is Amazon Elastic Map/Reduce (EMR). Other Hadoop-as-a-Service competitors include Mortar Data, Qubole, and recently Microsoft with Hadoop on Azure. Rackspace is about to launch its own Hadoop-as-a-Service offering based on Hortonworks' distribution.

[ What Open Source Hadoop Coming to Windows Means to IT ]

Jeff Vance is a freelance writer based in Santa Monica, Calif. Connect with him on Twitter @JWVance or by email at jeff@sandstormmedia.net.

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This story, "10 hot big data startups to watch" was originally published by CIO.


Copyright © 2013 IDG Communications, Inc.

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