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The Evolving Market for Commercial Software Built On Open Source
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![](https://www.linux.com/images/stories/41373/Structure-event-photo.jpg)
>Attendees listen to a presentation during Structure at the UCSF Mission Bay Conference Center, where Structure Data 2016 will take place. Image credit: Structure Events.
It's really hard to understate the impact of open source projects on the enterprise software market these days; open source integration became the norm so quickly we could be forgiven for missing the turning point.
Hadoop, for example, changed more than just the world of data analysis. It gave rise to a new generation of data companies that created their own software around open source projects, tweaking and supporting that code as needed, much like how Red Hat embraced Linux in the 1990s and early 2000s. And this software is increasingly delivered over public clouds, rather than run on the buyer's own servers, enabling an amazing degree of operational flexibility but raising all sorts of new questions about licensing, support, and pricing.
We've been following this closely over the years when putting together the lineup for our Structure Data conference, and Structure Data 2016 is no exception. The CEOs of three of the most important companies in big data operating around Hadoop -- Hortonworks, Cloudera and MapR -- will share the stage to discuss how they sell enterprise software and services around open source projects, generating cash while giving back to that community project at the same time.
There was a time when making money on enterprise software was easier. Once purchased by a customer, a mega-package of software from an enterprise vendor turned into its own cash register, generating something close to lifetime income from maintenance contracts and periodic upgrades to software that became harder and harder to displace as it became the heart of a customer’s business. Customers grumbled about lock-in, but they didn't really have much of a choice if they wanted to make their workforce more productive.
That is no longer the case. While an awful lot of companies are still stuck running immense software packages critical to their infrastructure, new projects are being deployed on cloud servers using open source technologies. This makes it much easier to upgrade one's capabilities without having to rip out a huge software package and reinstall something else, and it also allows companies to pay as they go, rather than paying for a bunch of features they'll never use.
And there are a lot of customers who want to take advantage of open source projects without building and supporting a team of engineers to tweak one of those projects for their own unique needs. Those customers are willing to pay for software packages whose value is based on the delta between the open source projects and the proprietary features laid on top of that project.
This is especially true for infrastructure-related software. Sure, your customers could install their own tweaks to a project like Hadoop or Spark or Node.js, but there's money to be made helping those customers out with a customizable package that lets them implement some of today's vital open source technologies without having to do all of the heavy lifting themselves. Just look at Structure Data 2016 presenters such as Confluent (Kafka), Databricks (Spark), and the Cloudera-Hortonworks-MapR (Hadoop) trio.
There's certainly something to be said for having a vendor to yell at when things go wrong. If your engineers botch the implementation of an open source project, you've only yourself to blame. But If you contract with a company that is willing to guarantee certain performance and uptime metrics inside of a service-level agreement, you're willing to pay for support, guidance, and a chance to yell at somebody outside of your organization when inevitable problems crop up.
The evolving market for commercial software on top of open source projects is something we've been tracking at Structure Data for years, and we urge you to join us in San Francisco March 9 and 10 if this is a topic near and dear to your heart.
--------------------------------------------------------------------------------
via: https://www.linux.com/news/enterprise/cloud-computing/889564-the-evolving-market-for-commercial-software-built-on-open-source-
作者：[Tom Krazit ][a]
译者：[译者ID](https://github.com/译者ID)
校对：[校对者ID](https://github.com/校对者ID)
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
[a]: https://www.linux.com/community/forums/person/70513

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构建在开源之上的商业软件市场持续成长
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![](https://www.linux.com/images/stories/41373/Structure-event-photo.jpg)
> 与会者在 Structure 上听取演讲，Structure Data 2016 也将在 UCSF Mission Bay 会议中心举办。图片来源：Structure Events。
如今真的很难低估开源项目对于企业软件市场的影响；开源集成如此快速地形成了规范，我们没能捕捉到转折点也情有可原。
举个例子，Hadoop，改变的不止是数据分析的世界。它引领了新一代数据公司，它们围绕开源项目创造自己的软件，按需调整和支持那些代码，更像红帽在 90 年代和 21 世纪早期拥抱 Linux 那样。软件越来越多地通过公有云交付，而不是购买者自己的服务器，拥有了令人惊奇的操作灵活性，但同时也带来了一些关于授权，支持以及价格之类的新问题。
我们多年来持续追踪这个趋势，它们组成了我们的 Structure Data 会议，而 Structure Data 2016 也不例外。三家围绕 Hadoop 最重要的大数据公司——Hortonworks，Cloudera 和 MapR——的 CEO 将会共同讨论它们是如何销售他们围绕开源项目的企业软件和服务，获利的同时回报那个社区项目。
以前在企业软件上获利是很容易的事情。一个客户购买了之后，企业供应商的一系列大型软件就变成了它自己的收银机，从维护合同和阶段性升级中获得近乎终生的收入，软件也越来越难以被替代，因为它已经成为了客户的业务核心。客户抱怨这种绑定，但如果它们想提高工作队伍的生产力也确实没有多少选择。
而现在的情况不再是这样了。尽管无数的公司还陷于在他们的基础设施上运行至关重要的巨大软件包，新的项目被使用开源技术部署到云服务器上。这让升级功能不再需要去掉大量软件包再重新安装别的，同时也让公司按需付费，而不是为一堆永远用不到的特性买单。
有很多客户想要利用开源项目的优势，而又不想建立和支持一支工程师队伍来调整开源项目以满足自己的需求。这些客户愿意为开源项目和在这之上的专有特性之间的差异付费。
这对于基础设施相关的软件来说格外正确。当然，你的客户们可以安装他们自己对项目的调整，比如 Hadoop，Spark 或 Node.js，但付费可以帮助他们自定义包部署如今重要的开源技术而不用自己干这些活儿。只需看看 Structure Data 2016 的发言者就明白了，比如 Confluent（Kafka），Databricks（Spark），以及 Cloudera-Hortonworks-MapR（Hadoop）三人组。
当然还有一个值得提到的是在出错的时候有个供应商给你指责。如果你的工程师弄糟了开源项目的实现，那你只能怪你自己了。但是如果你和一个愿意保证在服务级别的特定性能和正常运行时间指标的公司签订了合同，你就是愿意为支持，指导，以及在突然出现不可避免的问题时朝你公司外的人发火的机会买单。
构建在开源之上的商业软件市场的持续成长是我们在 Structure Data 上追踪多年的内容，如果这个话题正合你意，我们鼓励你加入我们，在旧金山，3 月 9 日和 10 日。
--------------------------------------------------------------------------------
via: https://www.linux.com/news/enterprise/cloud-computing/889564-the-evolving-market-for-commercial-software-built-on-open-source-
作者：[Tom Krazit ][a]
译者：[alim0x](https://github.com/alim0x)
校对：[校对者ID](https://github.com/校对者ID)
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
[a]: https://www.linux.com/community/forums/person/70513