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Article
Walmart taps Hadoop to power new data-driven applications
New big data applications running in Hadoop systems are helping to fuel Walmart's quest for more revenue by mixing information from retail stores with online e-commerce data. Read Now
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Article
Hadoop cluster architecture requires focused approach for ROI
The manager of the Hadoop platform at RelayHealth advises others to stay focused on what will result in a return on investment when implementing and expanding Hadoop clusters. Read Now
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Article
Develop a plan before plunging into a Hadoop data lake
Depositing all your data in a Hadoop-based repository for analytics uses is an alluring option. But building a data lake isn't that easy, cautions consultant Wayne Eckerson. Read Now
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Article
How Western Union enabled Hadoop use in its operations
A Hadoop implementation isn't just about deploying a cluster and processing data. Find out what else Western Union had to do to absorb Hadoop into its operational processes. Read Now
Editor's note
Companies that need to process large and varied data sets frequently look to Apache Hadoop as a potential tool because it offers the ability to process, store and manage huge amounts of structured, unstructured and semi-structured data. The open source Hadoop framework is built on top of a distributed file system and a cluster architecture that enable it to rapidly ingest and process data for use in analytics applications; Hadoop clusters can also be easily scaled up by adding compute nodes based on commodity servers. But Hadoop isn't a cure-all system for big data application needs as a whole. And while big-name Internet companies like Yahoo, Facebook, Twitter and eBay are prominent users of the technology, and other leading-edge users are also taking advantage of it, Hadoop projects are new undertakings for many organizations.
Some industry analysts assert that Hadoop is still in its adolescent stages, a technology that requires more maturity and functionality before it's fully enterprise-ready. The release of the second-generation Hadoop 2 software in October 2013 added broader application support and features designed to improve cluster availability and scalability. Even so, Hadoop adoption remains relatively low. For example, only 10% of the 284 respondents to a 2015 Gartner survey said their organizations were using it in production applications; another 16% said they were running pilot projects or experimenting with Hadoop, but 54% had no plans to use the technology.
Although Hadoop is open source software, it's by no means free. Companies implementing a Hadoop cluster generally choose one of the commercial distributions of the big data framework, which poses maintenance and support costs. Typically, it also must be used in coordination with a range of complementary technologies from what is referred to as the Hadoop ecosystem. As a result, prospective users have to hire experienced programmers or train existing employees on working not only with Hadoop, but also with MapReduce and related technologies such as Hive, HBase, Spark and Pig.
For many people, big data deployments and Hadoop projects are one and the same. That isn't the case, but Hadoop does have a central role to play in many big data management and analytics initiatives. Learn more about the Hadoop framework in this guide, which offers different perspectives on Hadoop's capabilities and looks at the technology's ongoing development, how it can benefit users and where it doesn't fully measure up to IT needs.
1Keeping up with Hadoop news and trends
As with other technologies, Hadoop is continually evolving to meet shifting big data management needs and business goals. The articles in this section catalog Hadoop technology trends, offering a look at new functionality, expanding applications and supporting tools in the Hadoop ecosystem.
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Article
The Hadoop vs. Spark debate: Companion or competitor?
Apache Spark can be used both in big data applications and as a standalone service. We asked IT professionals how they think this will affect Hadoop. Read Now
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Article
Hadoop's original core no longer mandatory cluster components
Hadoop vendors are adding technologies that look beyond the Hadoop Distributed File System for some uses, enabling clusters to be built without either HDFS or MapReduce. Read Now
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Article
SQL query engines open up path to broader Hadoop adoption
Hadoop is still at the proof-of-concept stage in many organizations. But some are using new SQL-on-Hadoop tools designed to simplify use of the framework through SQL querying. Read Now
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Article
'A lot of maturity' needed to enable wider use of Hadoop
Hadoop usage will continue to grow, predicts consultant Joe Caserta. But first, he says, the technology and related tools need to address some maturity challenges. Read Now
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Article
Implementing Hadoop: Storage considerations
Get advice on the issues to take into account in deciding which types of storage systems to use as the primary storage layer for Hadoop data. Read Now
2Examining issues and weaknesses in the Hadoop ecosystem
While many users find Hadoop projects to be cost-effective and useful, they have some drawbacks to keep in mind in assessing whether it's the right technology for an organization. In this section, users and analysts discuss where Hadoop falls short, particularly in terms of real costs, ease of management, performance and overall capability, and offer advice on how to avoid problems on deployments.
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Article
Game on, thanks to new Hadoop cluster management software
Mobile gaming company Chartboost needed a way to better optimize its processing workloads. Software from startup Pepperdata proved to be the answer. Read Now
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Article
Don't get dragged under by a Hadoop data lake project
Read about the lessons that several IT managers learned while deploying Hadoop-based data lakes, including the need for new skills and IT and data management processes. Read Now
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Article
To-do list for data lakes: Get more efficient, not so 'messy'
Forrester analyst Mike Gualtieri says Hadoop data lakes could become a viable alternative to traditional data warehouses -- if I/O and data governance improvements materialize. Read Now
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Diving into a data lake? Don't forget about Hadoop security
Hadoop isn't a single technology stack from a single vendor -- which makes it more difficult to develop security capabilities. But some help is on the horizon. Read Now
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Article
Hadoop still not up to handling real-time analytics?
Software vendors are adding query engines that run on top of Hadoop in an effort to turn it into a real-time data analysis platform. But some roadblocks remain. Read Now
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Article
Big data without bottlenecks: Avoiding Hadoop throughput snafus
While various issues can bog down the performance of Hadoop systems, there are ways to steer clear of the pitfalls and ensure that your big data applications keep cruising along. Read Now
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Article
When Hadoop is the right technology to use -- and when it's not
There's no shortage of hoopla about Hadoop, but it isn't the answer to all big data application needs. Smart companies need to make sure it's a good match for their requirements. Read Now
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Article
Facing up to issues with MapReduce and Hadoop
Big data users can't wish away the challenges of deploying systems based on Hadoop and MapReduce. But taking some good first steps helps minimize the difficulties. Read Now
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Article
Hadoop data in motion adds challenges for operational BI uses
Developers and data architects building operational business intelligence applications may need to create fast messaging infrastructures to handle streams of Hadoop data. Read Now
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Article
Analytics users find pros and cons with Hadoop
There are potential advantages to using Hadoop in analytics applications, but it also can pose some hardships that prospective users should be aware of up front. Read Now
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Article
Panelists discuss pitfalls of Hadoop, other big data technologies
A panel of technology vendors and analysts weighs in on the upsides and downsides of technologies such as Hadoop and MapReduce. Read Now
3Analysis of Hadoop and big data technologies
Watch the video interviews in this section for analyses and insights into the issues involved in evaluating, deploying and managing Hadoop tools and big data technologies. Well-known consultants and industry analysts share tips on adoption of Hadoop and other big data tools and on how to implement successful big data management and analytics programs.
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Video
Examining Hadoop adoption rates -- and why they aren't higher
What's slowing the adoption of Hadoop? SearchDataManagement editors take a look at the obstacles facing the big data framework in mainstream organizations. Watch Now
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Video
Hadoop industry initiative focuses on better interoperability
Now that organizations are getting a handle on using big data, attention is shifting to Hadoop interoperability. But a vendor initiative on that could end up causing a schism. Watch Now
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Video
White: Don't get misled by hype in selecting a Hadoop platform
Consultant Colin White discusses the maturity of Hadoop tools and details some of the key issues to consider when evaluating Hadoop distributions. Watch Now
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Eckerson: Hadoop can bring big data ROI for users
TechTarget analyst Wayne Eckerson discusses the potential benefits and challenges of using Hadoop systems to run big data applications. Watch Now
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Rogers: Skills shortage impedes adoption of big data tools
Shawn Rogers of Enterprise Management Associates explains a common roadblock to adoption of big data systems and technologies -- a lack of big data skills in organizations. Watch Now
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McKnight: Getting started with big data analytics
Consultant William McKnight discusses big data basics, offering practical advice on key issues related to big data management and analysis. Watch Now
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Eckerson: Tips on using big data analytics software and tools
Wayne Eckerson offers advice on using big data analytics technology and shares his view of the big data big picture. Watch Now
4Test your understanding of the Hadoop ecosystem
Take this brief quiz to see what you have learned about Hadoop.