Looking at the current batch of big data high flyers, from TenGen to Cloudera to Horton Works, each seems to be vying for the same kind of ubiquitous usage that enabled MySQL to get a more than 20x multiple. What they don't realize is that the failure of early open source acquisitions to deliver substantial value to owners has made buyers much more wary.
Companies like MySQL were valued based on a mystical belief that downloads could be monitized (not unlike the similarly wishful belief in monetizing eyeballs that motivated disastrous dot com acquisitions in the 90s). Moving forward, open source companies will be valued the old-fashioned way: by the viability of their business model.
Here are the top three places most big data open source companies are missing the boat:
- Prioritizing business model behind buzz: although buzz is critical for adoption growth, a viable business model trumps all in positioning a company for IPO or acquisition. First and foremost, this means being able to charge significant prices for add-on product pieces that customers want, such as security, clustering and monitoring.
- Confusing services with sales: low margin services revenues are no substitute for high quality license revenues. More importantly, companies that build up large services teams often neglect to fully integrate their product, as product integration provides a driver for services engagement. This lack of product maturity in turn prevents customers from being willing to pay much for the product itself - a classic vicious cycle.
- Hoping for a desperate buyer: companies that purchased open source players have by and large to translate open source leadership into commercial market share. The open source downloads generate lots of buzz but little license revenue, saddling their owners with an expensive, services-led business. In the immortal words of Mitt Romney, hope is not a strategy (although it *did* turn out to be an ok strategy for the incumbent in that case).