Managing and analyzing big data -- the exponentially growing body of information collected from social media, sensors attached to "things" in the Internet of Things (IoT), structured data, unstructured data, and everything else that can be collected -- has become a massive challenge. To tackle the task, developers have created a new set of open source technologies.
The flagship software, Apache Hadoop, an Apache Software Foundation project, celebrated its 10th anniversary last month. A lot has happened in those 10 years. Many other technologies are now also a part of the big data and Hadoop ecosystem, mostly within the Apache Software Foundation, too.
Spark, Hive, HBase, and Storm are among the options developers and organizations are using to create big data technologies and contribute them to the open source community for further development and adoption.
Some of these technologies are in production at enterprises such as Netflix and LinkedIn. They enable organizations to work with massive amounts of data in real time and turn that data around to improve services for end customers.
[Want to learn more about Hadoop? Read Hadoop At 10: Milestones And Momentum.]
These big data technologies often are born within organizations that are trying to enhance the way in which big data technologies work and improve their speed. They represent an evolution of the ecosystem, and the next wave of open source technology, which proves that development by a community of smart participants can be better than development within a propriety corporate environment.
This modern era of open source and big data all started with Hadoop, most often described as an open source framework for distributed storage and processing of large sets of data on commodity hardware.
"Hadoop created this center of gravity for a new data architecture to emerge," Shaun Connolly, VP of corporate strategy at Hadoop distribution company Hortonworks, told InformationWeek in an interview. "Hadoop has this ecosystem of interesting projects that have grown up around it."
And the evolution continues. New projects are accepted into the Apache Software Foundation's big data ecosystem all the time. Most recently, Apache Arrow became a Top-Level Project. Other projects may enter the ecosystem as part of the Apache Software Foundation's Incubator. IBM's SystemML machine learning engine for Spark gained acceptance as an Incubator project late last year.
There are many projects that are part of the Apache Software Foundation's big data ecosystem. Here's a look at some of the significant ones, and a peek at a few up-and-comers. Once you've reviewed our choices, let us know what you think in the comments section below. Are there any you prefer? Are there some we've missed? We'd love to hear from you.
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