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Data Storage & Management
Data Storage & Management news, information, and how-to advice
5 things we hate about Spark
MariaDB pops up on Azure with new cluster service
Oracle fixes critical flaws in Database Server, MySQL, Java
The bad news: Java and Oracle's database products had lots of vulnerabilities. The good news: None are currently under attack.
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.
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
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.
Review: MongoDB 3.0 reaches for the enterprise
MongoDB zeroes in on operations with pluggable storage engines and revamped management tools
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.
Why streaming analytics is such a big deal
Analytics drive decisions, but some decisions shouldn't wait until batch processes complete -- which is why, eventually, we'll all analyze data as it streams in.
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.
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.
LinkedIn fills another SQL-on-Hadoop niche
LinkedIn's open source, home-brew OLAP project is a new way for Hadoop users (and others) to query both real-time and historical data.
Spark and Storm face new competition for real-time Hadoop processing
DataTorrent is releasing its real-time data processing engine for Hadoop and beyond as the open source Project Apex.
Review: Storm’s real-time processing comes at a price
Storm may be the only real-time processing framework that has been proven to process millions of messages per second, but there's a steep learning curve ahead.
Spark, big data's brightest star, needs to grow up
Spark is the hottest project in big data -- but Databricks, the company behind it, needs to ensure its implementation has a plausible path to maturity.
What you need to know about Hadoop right now
Andrew updates his cheat sheet for developers navigating the ever-expanding Hadoop ecosystem. Storm and Spark still top the list, but don't miss new additions like Phoenix, Kafka, and Falcon.
First look: MongoDB 3.0, for mature audiences
The new MongoDB features document-level locking, better write performance, big memory support, and more. At last, MongoDB is all grown up.
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