0xdata extends Hadoop abstraction layer with Scala support
Abstraction is key to effective enterprise analytics, with most companies unable or unwilling to hire a team of statisticians possessing the necessary know-how to make sense of their massive data troves. An emerging startup called 0xdata is trying to fill this talent gap with a unique machine learning platform that abstracts the complexity of MapReduce to make insights more accessible throughout an organization.
The firm’s flagship H2O offering runs sophisticated algorithms on a speedy in-memory caching engine that lets users access information in HDFS using tools that they’re already familiar with, namely Excel, the RStudio development platform and JSON. The software also makes it easier to combine data from multiple multiple sources, including object stores such as Amazon S3 as well as SQL and NoSQL systems.
H2O has recently been augmented for support for Scala, an increasingly popular programming that enables developers to implement predictive algorithms like classifications, regressions and decision trees and run them efficiency in distributed environments. It has the added benefit of being based on Java, the language Hadoop is implemented in.
SriSatish Ambati, the founding CEO of 0xdata, said in a statement, “We have deep roots in the Java community and Scala has easily become one of the leading languages for Big Data. With open source H2O, Scala users can analyze distributed in-memory data sets and run wickedly fast intelligent applications and data products.” Ambati added, “We are JIT’ing JVM friendly code for Scala designers and made it simple to add massively scalable predictive analytics to any application architecture built on the JVM runtime.”
Before 0xdata, Ambatio founded Platfora, another Hadoop abstraction startup that builds business intelligence solutions. The latest release of the company’s Big Data Analytics Platform launched in November with a first-of-its-kind event stream analysis tool and an object-based “data catalog” that structures information around customers, products and other points of interest.
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