This week’s Oracle World was bracketed by two events. First: the unveiling of Oracle Exalytics, a beefy in-memory appliance dedicated to large-scale analytics, during Larry Ellison’s opening keynote. Second: the undressing of Oracle’s cloud computing initiatives by Marc Benioff, SalesForce’s CEO, and the unceremonious cancellation of his keynote on Wednesday morning.
Both events highlight that when it comes to Big Data, analytics and cloud computing, Oracle is on the wrong side of history.
Startups don’t use Oracle
To glimpse the future of the data stack, Oracle need look no further than its own backyard, to what Silicon Valley start-ups are embracing: the distributed processing ecosystem of Hadoop, NoSQL data stores like MongoDB, and cloud platforms like Amazon’s web services. As Marc Andreessen said last week, “Not a single one of our startups uses Oracle.”
The truth is, Oracle can’t support the kind of technology stacks embraced by startups — open-source software, elastic architectures, commodity hardware grids — because it cannibalizes revenue from their existing lines of business.
“I don’t care if our commodity X86 business goes to zero,” Ellison said in Oracle’s last earnings call, “We don’t make money selling that.”
This commoditization wave has sent others, including HP, fleeing from hardware, but it has driven Oracle into the breach as a big box retailer: they’re attempting to capture higher margins on sales of SPARC architectures.
But history is not on Oracle’s side. Here are four realities that Oracle must face to maintain its unassailable position as the world’s leading data firm:
#1: The future of data is distributed
“Lots of little servers everywhere, lots of little databases everywhere. Your information got hopelessly fragmented in the process.” – from Matthew Symonds book Softwar (p. 38).
This is how Larry Ellison described the technology landscape of the 1990s, and his personal jihad against complexity has deepened Oracle’s distrust of distributed computing.
But the tide of data isn’t turning back, and the scale is too large to contain in any box; Big Data, on the scale of hundreds of terabytes to petabytes, must be distributed across “lots of little servers.” The most viable tool available today for processing and persisting Big Data is Hadoop.
Whether at the data layer — or a level above, at analytics — firms must adapt to this distributed reality and build tools that enable parallelized, many-to-many migration of data between nodes on Hadoop and those on their own platforms.
#2: The future of computing is elastic
Metal server boxes don’t bend or expand; they are inelastic, both physically and economically. In contrast, the needs of businesses are highly elastic; as companies grow, they shouldn’t have to unpack and install boxes to meet their compute needs, any more than they should install generators for more electricity.
Computing is a utility, compute cycles are fungible, and firms want to pay for what they need, when it’s needed, like electricity.
The ability to scale storage and compute capacity up or down, within minutes, is liberating for individuals and cost-effective for organizations, but it is impossible with a “cloud in a box.” It is only enabled by a true cloud computing infrastructure, with virtualization and dynamic provisioning from a common pool of resources.
#3: The future of applications isn’t the desktop
Despite Oracle having developed the first pure network computer in 1996 (or perhaps because of this), far too many of Oracle’s supporting business applications are delivered via the desktop, rather than via web browsers.
By comparison, Cloudera has created a rich web-based application for managing and monitoring all aspects of Hadoop clusters; Amazon Web Services has a fully-featured web console for interacting with its offerings; and Salesforce’s products are almost exclusively web-driven.
The expressivity afforded by web browsers has risen dramatically in the last two years, particularly with the emergence of Javascript as the lingua franca of web application development, and improvements in Javascript engines.
The same trend from desktop to browser also extends into mobile devices. An increasingly large fraction of computing occurs on smart phones and tablets, and forward-thinking firms, like Dropbox, have built applications that cater to this reality.
#4: The future of analytics is visual
The decades of disappointment with business intelligence tools isn’t due only to their lack of brains (such that they’ve now fled to the fresh moniker of “business analytics”), but also the absence of beauty. Data is beautiful, as any reader of Edward Tufte can attest.
When visualized thoughtfully and artfully, data has an almost hymnal power to persuade decision makers. And when exploring data of high complexity and dimensionality, the kind that lives in Oracle’s databases, tools that accelerate the “mean time to pretty chart” are essential.
In addition, analytics tool users are right to expect a smooth user experience on a par with other tools, whether photo editing or word processing, when they are creating and exploring data visualizations.
Yet amidst all of Oracle’s presentations and marketing materials about big data and analytics, one finds not a single dashboard or visualization to stir the senses.
While Spotfire and Tableau are notable exceptions to this critique, on the whole, the tools that dot the Oracle landscape lack either brains or beauty.
Enterprises will be slow to wake up to these realities, and Oracle will continue to profit handsomely from their slumber.
Fin: Oracle is ripe for attack by data services
The opportunities abound to chip away at the massive market share that Oracle now holds, providing data services to start-ups who won’t buy Oracle’s capital intensive boxes, and helping medium-sized businesses migrate to flexible, cost-effective, cloud-based alternatives.
(An earlier version of post was published as a guest column at GigaOm).