78 Open Source Replacements for Expensive Applications

'Back when Datamation first started making lists of open source software that could replace expensive proprietary applications, most commercial software came in a box and required a flat fee for purchase. These days, with the advent of cloud computing and software as a service, most applications require a regular monthly or yearly subscription. Those subscriptions make it seem like software has become more affordable. After all, $10 or $20 a month doesn't seem like a lot. But when you add up those repeating fees, users often pay more under the new subscription plans than they did under the old flat-fee arrangements. If you use a lot of different applications, those fees can quickly add up. And it can be particularly hard to justify the expense for a piece of software that you only use once in a while. Open source software offers an alternative to paying those high fees. And in many cases, the open source options are as good as or better than the comparable commercial, proprietary solutions. In fact, in the most recent BlackDuck Future of Open Source Survey, the top reasons why people said they use open source software were because of the features, freedom from vendor lock-in and the quality of the solutions. Price and total cost of ownership weren't even on the list. In other words, people are using open source because the software is so good, and the fact that it is free is just a side benefit. The list below includes a variety of open source software for home users, SMBs and large enterprises. All of these applications can replace commercial products that can carry high prices. Even if buyers choose to purchase support or other services for their open source software, the open source options are generally much more affordable than the comparable proprietary solutions.' -- source: http://www.datamation.com/open-source/78-open-source-replacements-for-expens... Cheers, Peter -- Peter Reutemann Dept. of Computer Science University of Waikato, NZ +64 (7) 858-5174 http://www.cms.waikato.ac.nz/~fracpete/ http://www.data-mining.co.nz/
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Peter Reutemann