Amazon and commercial open source in the cloud: It’s complicated

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Curated from zdnet.com →

Like many platform operators, Amazon has a love-hate relationship with those hosted on its platform. This is particularly true for open-source software creators, who see their products on offer on Amazon’s cloud on terms they are not happy with.

It’s a complicated relationship, which touches upon many aspects of technology, law, and social norms. The issue started becoming more pronounced and entering our turf on Big on Data as Amazon Web Services (AWS) started offering top open-source data management products on its platform.

Vendors developing those open source products started accusing AWS of strip mining, i.e., reaping the benefits of the products, without contributing back to their development. Google stepped in to show there is another way of doing business with open source in the cloud. TheNew York Times stepped in and made this talk of the town.

This is huge, as much as it is complicated. Let’s try and unpack it.

AWS is the technology branch of Amazon. AWS pioneered the cloud in the early 2010s, based on the premise of renting out spare compute and data capacity from Amazon’s servers. By now, the cloud is the dominant way of storing data and doing compute.

AWS is not just the main source of Amazon’s operating income at $40 billion in 2019. Amazon CEO Jeff Bezos describes Amazon as a technology company. The technological prowess AWS brings to Amazon is at the heart of Amazon’s expansion to the aftermarket. AWS powers countless products and services every day. When AWS hiccups, the world notices.

Like AWS, open-source software today is ubiquitous. Open source predates Amazon, as much as it enables it. Open source such as the Linux operating system is what powers most data centers today, including AWS. Cloud, data, and open-source converge.

The future of databases is the cloud. But the future of databases is also something else: It is open source. By 2022, more than 70% of new in-house applications will be developed on an open-source database, and 50% of existing proprietary relational database instances will have been converted or be in the process of converting.

Historically, as open-source software (OSS) started becoming more complex and successful, different ways to monetize it started emerging, too. This makes sense: Software takes time and expertise to develop. While some people may develop OSS as a side gig, complex software requires dedication. Dedication requires financial support, hence, monetization.

In some cases, OSS projects are collaborations cross-cutting many organizations. Typically, this happens when many organizations are interested in developing something. Open source fosters collaboration and ensures the result can be used by everyone. Contributors are paid by organizations that employ them, and monetization is not an issue.

But what happens when a project gets a life of its own, and/or some contributors wish to go their way, and monetize the project? Offering services around the project is one way. Many SMBs and freelancers do this — not necessarily the ones who built the software. The fact that OSS is free to use makes skills built around it transferable, which is a big advantage.

OSS builders enable technologist experts who use the software to monetize their services. This can be a symbiotic relationship, as technologists may help expand the software’s user base and contribute knowledge in the form of documentation or question answering or even some code. Often, OSS builders and expert technologists using the software largely overlap.

But the more complex the software, the bigger the organization needed to build it. Service-based business model margins are relatively poor and do not scale well. Notoriously, only Red Hat has succeeded in building a sustainable business around complex OSS on a service-based business model. Even though Red Hat’s scale is tremendous, eventually even Red Hat chose to accept IBM’s acquisition offer.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.