why aren't all 14 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Prediction Not checkable as stated
Mike Olson predicts MapReduce compute cycles in Hadoop clusters will approach zero
“I think the percentage of cycles spent on MapReduce in Hadoop clusters generally is going to asymptotically approach zero. That's not because there will be less MapReduce happening, but because there will be so much of the other stuff happening.”
Insight
Cloudera uses proprietary management tools to prevent commoditization by large vendors
“Because we've got some management monitoring administrative tools That the big, well-capitalized vendors can't simply pick up and use against us. We've got a reason for customers to come and talk to us. It's not really about lock-in. It's about lock-out for IB…”
Prediction Not checkable as stated
Big data market has the potential to surpass relational database market size
“I think that there's an opportunity for the big data market to be much bigger than the relational database market was, right?”
Insight
Only hybrid open-source models generate sufficient margins to fund platform innovation
“I am convinced that Only a hybrid company can basically generate the revenues and the margins that allow us to invest forward in innovation in the platform.”
Prediction Held up
Majority of big data market spend will go to applications, not platforms
“The lion's share of the money spent in the market Is going to be for apps, not for the platform.”
Insight
Hadoop was designed for new data problems, not relational database issues
“What we didn't understand at the time, and it's been a pretty common feeling, is Hadoop wasn't built to solve the problem we'd been solving with relational databases. It was designed to solve a new problem, and it turned out that new problem was going to be ve…”
Assertion Not checkable as stated
Hadoop's shared-nothing architecture does not easily translate to OLAP or OLTP workloads
“Hadoop, this big scale-out, shared-nothing architecture, is good at much, but that architecture doesn't easily translate into OLAP or OLTP workloads.”
Assertion Supported
Intel acquired an 18 percent equity stake in Cloudera for $740 million
“Intel spent seven hundred forty million dollars and acquired an 18% stake in Cloudera.”
Assertion Supported
IBM began offering open-source alternatives within 2.5 years of Cloudera's founding
“At two and a half years, IBM was looking at what we were doing and offering their own open source alternatives, so.”
Disclosure
Cloudera refuses to acquire companies or products that compete with open source
“So in general, we won't acquire stuff that competes with existing open source, because that would be crazy, right?”
Disclosure
Sleepycat Software operated for eight years without venture capital before Oracle acquisition
“Sleepy Cat was the company that commercialized Berkeley DB in 98, and we ran that company entirely independent, no venture capital the old-fashioned way. We would make money and then we would spend it for eight years. We sold the company to Oracle in 2006”
Assertion Partly supported
Annual spend on relational database tools is double the underlying platform spend
“Seventy billion annually is spent on services and applications and tools on top, right? So more than twice as big as the platform play is The tools play.”
Assertion Supported
Hortonworks' IPO matched its prior private valuation after a 60 percent spike
“Horton's IPO was exceptionally run, right? I mean, you know, A nice sixty-plus percent spike in the stock up to mid-twenties. It re-achieved the valuation that it had hit in private investment prior.”
Assertion Not checkable as stated
Splunk and Tableau were the only public big data stocks before Hortonworks
“Prior to Hortonworks IPO, you could go buy some Splunk, or you could buy Tableau, and there was really nothing else that was big data.”