“One does not discover new lands without consenting to lose sight of the shore for a very long time.” -André Gide
Ever heard of Eclipse, OpenOffice, Hadoop, Android, Firefox or MySQL? If so, can you identify the common denominator between these software tools and applications? If you answered, “They’re all open source,” you’re right!
While open source (OS) software has been around a long time, many organizations have been somewhat slow on the draw to integrate OS into their enterprise infrastructure. Some companies have considered commercial OS solutions alongside other proprietary solutions for initiatives such as BI/DW, and compared them on functionality and cost – if they’ve considered OS at all. The truth is: We know about these traditional OS solutions, but we’ve been able to get by without them.
It’s important to note that while OS software is free and (typically) easy to install, commercial OS vendors have to make their money somehow. They can do this in a variety of ways: develop custom/proprietary code to enhance the free software; provide custom design and development services; provide a development sandbox; host software installations; and offer technical support and training. As with proprietary software, OS software also requires ongoing support and maintenance. It won’t always be cheap.
A Big Data Best Practice for Open Source Adoption
With the rapid growth of big data solutions these last few years, OS has taken a significant step forward into the enterprise space. Conversely, more and more enterprise-level organizations have begun to participate in and contribute code to the OS community. The time has come to take open source seriously for big data platforms.
The primary reason is that many – if not most – of your current software vendors have integrated a variety of OS projects into their own proprietary big data solutions. Not only has Hadoop been integrated, but also many Hadoop-related projects, such as Hive, Hbase and Mahout. Vendors are also partnering with key big data service providers, such as Cloudera, HortonWorks, MapR, and other niche shops to support their customers’ emerging big data needs.
Make no mistake: We’re in geek heaven right now. Open source solutions are here to stay in the big data world.
Key Takeaways for Marketers
- If you’re talking about big data technology, you’re probably talking about open source software.
- Hadoop was built by developers for developers, not marketers. Don’t tackle alone.
- Open source software is free, but that’s where “free” stops. It costs to implement.
- Visit the graveyard near the southern tip of the island. It has open gravesites.
- Find out what your company’s position is on open source software and big data. One will most likely inform the other.