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6 Cloud, Big Data Startups To Watch

Check out what the Structure 2013 LaunchPad winners can do with cloud, big data problems.

That opens the door for startups basing their infrastructure on App Engine to build out a compatible infrastructure as a private cloud operation as they mature and bring more operations in-house. App Engine remains a relatively young setting for enterprise workloads. It didn't come out of beta until June 2012. But the future of an App Engine-style private cloud is not yet part of the AppScale product line and Rollins made no mention of such a possibility in his presentation. He stuck to the failover use case.

"Wouldn't it be worth $1,000 a year to make sure your application never fails?" he asked.

"AppScale has done a lot to replicate Google App Engine with a very small team," noted Robles, but the failover use case failed to win over the other two judges.

Three of the entrants were focused on data management and extracting more meaning out of the big data being collected today.

Mocking the SQL query language as 1978 technology, CTO Matthias Brantner of startup 28msec said it's time for a more real time, more flexible and broader data type reading query language, such as open-source JSONiq.

The name is taken from JSON or JavaScript Object Notation, frequently used by NoSQL systems to capture and exchange large amounts of both structured and unstructured data. The NoSQL systems MongoDB and Cassandra both support use of JSON, and JSONiq brings commands such as Project, Join, Group and Filter to data management.

"We've been mostly gluing and stitching data together using 1978 technology," said Brantner, referring to the year that IBM researcher Edgar Codd first published his paper on using mathematical set theory to build SQL. IBM didn't release it as a query language product until DB2 was ready eight years later. Brantner said it's time for a new generation of data management systems to take over from relational databases. His firm's 28.io data management system with JSONiq querying became available Thursday. It can retrieve data from "any system," the firm claims on its website, and Brantner said it works with both relational and NoSQL systems.

With a freely available extension, JSONiq can retrieve XML-based data. Brantner said the 28.io system captures XML, transforms it into JSON formatting and stores it on Amazon's S3 storage service. It is available either as a subscription service from the Palo Alto company or as software to be installed on-premises.

Brantner spoke with conviction on the need to implement new data management platforms, such as 28.io, in a Web- and mobile application-based world. He and his team have been working on 28.io in stealth mode for seven years.

Brantner received a Ph.D. in information systems from the University of Mannheim in Germany. While there, he conducted research on "Rewriting Declarative Query Language" and previously worked on XQuery systems that extracted data from XML databases.

MetricaDB founder and CEO David Crawford said his firm is offering an online data-analysis service, able to draw data from SaaS applications, Google Analytics, Tumblr, Facebook, Twitter, Stripe and Zendisk, as well as NoSQL and relational database sources, and then analyze it for meaningful information.

Many businesses, having found they can collect big data from such sources, "are throwing people at the problem" of trying to find meaning in the data. MetricaDB supplies the interface to the data-collecting system, then lets the user analyze the data. "We are the analytics platform for the new data-based world," Crawford said.

Another analytics approach was supplied by Synapsify. Stephen Candelmo, co-founder and CEO, said his Washington, D.C.-based firm used a small team of six to develop a patented method of text analytics. Its approach "moves beyond simple keyword extraction" to identify the credibility of a text and the seriousness or gravitas with which it is addressing a subject.

It can deal with short comments on the Web or book-length manuscripts. It curates a given text against competing sources. It has five pilot clients using its service on AWS.

Judge Sinha commented that Synapsis had impressive technology but needed to find a use case where its capabilities became a compelling business proposition.

In the judges' voting, Factor.io, MetricaDB and 28msec all tied for second place.

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