Hadoop

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Tame unruly big data flows with StreamSets

See how the free open source StreamSets Data Collector brings visibility and control to real-time streaming data

Spark 2.0 takes an all-in-one approach to big data

With a new streaming system, performance enhancements, and API refinements, Apache Spark 2.0 offers a big umbrella to data users

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Redis plants the seeds for an open source ecosystem

Redis Modules help the caching and in-memory storage system work with new data structures and database behaviors

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Apache Beam wants to be uber-API for big data

New, useful Apache big data projects seem to arrive daily. Rather than relearn your way every time, what if you could go through a unified API?

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Why Spark 1.6 is a big deal for big data

Already the hottest thing in big data, Spark 1.6 turns up the heat. Here are the high points, including improved streaming and memory management

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16 for '16: What you must know about Hadoop and Spark right now

Amazingly, Hadoop has been redefined in the space of a year. Let's take a look at all the salient parts of this roiling ecosystem and what they mean

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10 things to worry about in 2016

Yes, it's the poignant sequel to last week's reprieve: a jolly list of worries to keep you up at night this holiday season

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5 things we hate about Spark

Spark has dethroned MapReduce and changed big data forever, but that rapid ascent has been accompanied by persistent frustrations

Hadoop is slowly eating conventional analytics

The components of the Hadoop ecosystem won't overthrow Teredata or IBM Netezza any time soon, but ultimately, the commodity solution almost always wins.

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Hadoop, in trouble? Only in Gartner-land

A new poll of customers provides a brighter, more detailed picture of Hadoop adoption than Gartner's famously downbeat survey.

Open source Java projects: Apache Spark

Set up and use Spark to analyze data contained in Hadoop, Splunk, files on a file system, local databases, and more.

How Apache Ranger and Chuck Norris help secure Hadoop

The Hadoop ecosystem has always been a bag of parts, each of which needs to be secured separately -- at least they did need that, until Apache Ranger came to town.

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The 7 most common Hadoop and Spark projects

Think you're breaking new ground with your Hadoop project? Odds are it fits neatly into one of these seven common types of projects.

9 big data pain points

Do enough Hadoop and NoSQL deployments, and the same problems crop up again and again. It's time for the industry to nail them sooner rather than later.

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Which freaking Hadoop engine should I use?

These four truths will help you determine which Hadoop technology to use for the types of workloads you anticipate.

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Big data, big challenges: Hadoop in the enterprise

Fresh from the front lines: Common problems encountered when putting Hadoop to work -- and the best tools to make Hadoop less burdensome.

Spark 1.4 adds support for R, Python 3, cluster management

Spark data processing framework adds languages used by many data crunchers, as well as container-based cluster management features.

A better mousetrap: A JSON data warehouse takes on Hadoop

Sure, a NoSQL or JSON data warehouse sounds faddish, but SonarW is a better solution for many.

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