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A Roundup of Cloudera Distribution Containing Apache Hadoop 5

by Alex Giamas on  Apr 18, 2014

Cloudera recently released the latest version of its software distribution, CDH5. Almost 20 months after the last major version, CDH4 seems like ages in the Big Data world. We take a look at new features this release brings and the future direction of Cloudera after the latest round of investment from Intel and Google Ventures.

Hadoop Gets Better Security, Several Operational Improvements

by Roopesh Shenoy on  Apr 18, 2014

Hadoop 2.4.0 was recently released with several enhancements to both HDFS and YARN. This includes support for Access Control Lists, Native support for Rolling upgrades, Full HTTPS support for HDFS, Automatic failover of YARN and other operational improvements

Hydra Takes On Hadoop

by Rags Srinivas on  Apr 11, 2014

The social-networking company AddThis open-sourced Hydra under the Apache version 2.0 License in a recent announcement. Hydra grew from an in-house platform created to process semi-structured social data as live streams and do efficient query processing on those data sets.

Spark Gets a Dedicated Big Data Platform

by Charles Menguy on  Apr 03, 2014

Spark users can now use a new Big Data platform provided by intelligence company Atigeo, which bundles most of the UC Berkeley stack into a unified framework optimized for low-latency data processing that can provide significant improvements over more traditional Hadoop-based platforms.

Rebecca Parsons on the ThoughtWorks Technology Radar

by Shane Hastie on  Mar 28, 2014 3

In January ThoughtWorks released the latest version of their Technology Radar in which they track what's interesting in the software development ecosystem. The big themes this year are (1) early warning systems and recovery in production, (2) the tension between privacy and big data, (3) the javascript ecosystem and (4) blurring of the line between the physical and virtual worlds.

Big Data Hadoop Solutions, State of Affairs in Q1/2014

by Boris Lublinsky on  Mar 04, 2014 1

According to a new Forrest report, Hadoop’s momentum is unstoppable. Its usage in the enterprise is continuously growing due to its ability to offer companies new ways to store, process, analyze, and share big data. The report takes a look at Hadoop vendors and ranks them.

Spark Officially Graduates From Apache Incubator

by Alex Giamas on  Feb 28, 2014

Recently, Spark graduated from the Apache incubator. Spark claims up to 100x speed improvements over Apache Hadoop over in-memory datasets and gracefully falling back to 10x speed improvement for on-disk performance. Based on Scala, it can run SQL queries and be used directly in R. It provides Machine Learning, Graph database capabilities and other further discussed in the article.

Elasticsearch 1.0.0 released

by Ralph Winzinger on  Feb 14, 2014

Elasticsearch released version 1.0.0 of its self-titled, open-source analytics tool. Elasticsearch is a distributed search engine which allows for real-time data analysis in big-data environments. The new version comes with various functional enhancements and changes to the API to make Elasticsearch more intuitive and powerful to use.

Design Patterns for Cloud-Hosted Applications

by Jan Stenberg on  Feb 11, 2014

The patterns & practices group at Microsoft have released a guide with solutions and patterns suitable when implementing cloud-hosted applications. The guide contains ten guidance topics together with 24 design patterns targeting eight categories of problems covering common areas in cloud application development. Also included are ten sample applications to demonstrate the usage these patterns.

Interactive SQL in Apache Hadoop with Impala and Hive

by Alex Giamas on  Feb 07, 2014

In the race for interactive SQL in Big Data environments, there are two open source based front-runners, Impala and Hive with the Stinger project. Cloudera recently announced that Impala is up to 69 times faster than Hive 0.12 and can outperform DBMS. Other than raw speed, we take a look at other considerations in choosing a SQL engine for Hadoop and also Tez, an application framework for YARN.

Spark, Storm and Real Time Analytics

by Alex Giamas on  Jan 31, 2014

Hadoop is definitely the platform of choice for Big Data analysis and computation. While data Volume, Variety and Velocity increases, Hadoop as a batch processing framework cannot cope with the requirement for real time analytics. Spark, Storm and the Lambda Architecture can help bridge the gap between batch and event based processing.

Google Improves Hadoop Performance with New Cloud Storage Connector

by Richard Seroter on  Jan 20, 2014

With a new connector, it is now possible for Hadoop to run directly against Google Cloud Storage instead of using the default, distributed file system. This results in lower storage costs, fewer data replication activities, and a simpler overall process.

New Education Opportunities for Data Scientists

by Charles Menguy on  Jan 14, 2014

2013 has been rich in announcements for new programs, degrees and grants for aspiring data scientists and Big Data practitioners.

Hadoop-as-a-Service Provider Qubole Now Runs on Google Compute Engine

by Michael Hausenblas on  Dec 28, 2013

Qubole, a managed Hadoop-as-a-Service offering is now available on Google Compute Engine (GCE). Qubole was so far only available on Amazon's AWS and this announcement follows only a few days after Google releasing GCE into general availability.

Hadoop Jobs on GPU with ParallelX

by Charles Menguy on  Dec 26, 2013 1

The MapReduce paradigm is not always ideal when dealing with large computationally intensive algorithms. A small team of entrepreneurs is building a product called ParallelX to solve that bottleneck by harnessing the power of GPUs to give Hadoop jobs a significant boost.

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