Guavus, a leading provider of big data analytics solutions for operational intelligence, has unveiled Reflex 2.0 with support for Apache Spark and Hadoop YARN. The Guavus Reflex™ Operational Intelligence Platform provides a real-time analysis across business and operations for better quality decision-making.
Databricks, the company founded by the creators of Apache Spark—the powerful open-source processing engine that provides blazingly fast and sophisticated analytics—announced today the launch of Databricks Cloud, a cloud platform built around Apache Spark. In addition to this launch, the company is announcing the close of $33 million in series B funding led by New Enterprise Associates (NEA) with follow-on investment from Andreessen Horowitz.
As the data world undergoes its Cambrian explosion phase, our data tools need to become more advanced to keep pace. Deep Learning has emerged as a key tool in the non-linear arms race of machine learning. In the video below Josh Patterson and Adam Gibson take a look at how we can parallelize Deep Belief Networks in Deep Learning on Hadoop’s next generation YARN framework with Iterative Reduce.
Elasticsearch, Inc., the company on a mission to make data useful to businesses by delivering an advanced search and analytics engine, has announced the 2.0 release of its Hadoop connector, Elasticsearch for Apache Hadoop, along with certification on Cloudera Enterprise 5.
Platfora, the Big Data Analytics platform that runs natively on Hadoop, today announced tremendous sales growth in excess of 200 percent in annual recurring revenue over the past 12 months.
Alteryx, a leader in data blending and advanced analytics, today announced during its Inspire 2014 keynote that analysts will soon be able to read data directly from the Hadoop Distributed File System (HDFS), blend it with other sources, perform advanced analytics, and then write enriched data back to HDFS with Alteryx Analytics.
For up-and-coming data scientists who need to get up to speed on Hadoop architectures, here is another in a long line of compelling Big Data & Brews episodes. In the video below we hear from three Hadoop luminaries about the Hadoop projects they’ve worked on – Erich Nachbar on Spark, Michael Stack on Hbase and Ari Zilka (from Hortonworks) on Stinger. Great insider’s perspective!
One of the attractions of the Hadoop Summit 2014 was the Big Data & Brews interview series – “Live from Hadoop Summit.” These short, well-focused discussions always provide good light into important industry trends. In the episode below, the conversation turns to the subject of SQL on Hadoop. Stefan Groschupf, the CEO of Datameer, recorded a special interview with Ovum analyst Tony Baer who gave his thoughts on the topic.
I found an interesting discussion going on in the Global Big Data & Analytics group on LinkedIn – “Why do Hadoop projects fail?” Having just returned from the Hadoop Summit 2014 in San Jose, I witnessed plenty of use case examples Hadoop implementations that were wildly successful. I was therefore intrigued by the notion to itemize causes for failed projects.