The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 18 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
Ghodsi: Any proprietary software company is ripe for open-source disruption
“Any proprietary software company out there is ripe for disruption by an open source competitor.”
Ghodsi: Early Big Tech achieved AI breakthroughs using 1970s algorithms with massive data
“What they were doing is they were taking those algorithms from the seventies that do not work, but they were applying orders of magnitude, more data to it. So a lot of data on modern hardware, and they were getting superhuman results.”
Ghodsi: Founders cannot pick their sales channel; product-market fit dictates it
“You don't get to pick your channel. You can, you don't get to say, oh, I want my ASP to be 50 K or 60. That's not your choice. You have a product. You have a market. If it has fit, you have to find the right channel to connect those two.”
Ghodsi: Databricks open-sources products only after achieving product-market fit
“So our secret sauce is look at an enterprise problem, figure out what that is, understand it deeply by being really customer obsessed, bring the problem back, have the innovators, the PhDs that know how to solve these problems. Solve the problem. Iterate quick…”
Ghodsi: Creating open-source software gives cloud hosts a competitive advantage
“We're going to host open source software in the cloud, but the difference is we'll create open source software. That way we get competitive advantage with respect to anyone else who would want to do the same thing, right? Otherwise anyone can pick up any open …”
Ghodsi: Open-source Lakehouses will eventually render proprietary data warehouses obsolete
“So slowly what's happening is that the open source realm An ecosystem is emerging where you can do all of your analytics in this lake house paradigm, and you don't, eventually it will be the case that you will not need all these other, you know, proprietary ol…”
Ghodsi: Snowflake coexists with Databricks in about 70% of accounts
“It's certainly going to coexist, and it already coexists with Databricks in probably 70% of the accounts we're in.”
Ghodsi: Enterprise demand starves new innovation unless R&D teams are separated
“So you actually, or chart wise should separate those out because otherwise what happens when you're successful is that the former gets all of the resources because the big enterprises have infinite demand for your for the things that you're doing.”
Ghodsi: Hadoop was terrible for machine learning tasks
“The people in Amplab that were doing machine learning, the math folks, they had to use this thing called Hadoop, which was just terrible.”
Ghodsi: Databricks' early reliance on product-led growth was a mistake
“On the channel side, the mistake with it is we really early on, we're really big believers in this product led growth. We said, you know, we're going to build this beautiful simplified product that we now have. We put it online and it's going to be cloud based…”
Ghodsi: Databricks will open-source lower-stack layers and build proprietary software above
“We're definitely going to continue to move up the stack and then commoditize the stuff that's below by open sourcing it and just releasing it to the market and making it the standard and then moving up the stack with innovations.”
Ghodsi: Databricks hires executive leaders who build, not just maintain
“What are the things we look for? We look for people who have seen build. So the joke I say is, do you have a driver's license? And people will say, I have it. Are you good at driving your car? Yes, I'm very good at it. Why are you asking? Can you build a car w…”
Ghodsi: Centralized data teams inevitably become operational bottlenecks
“As you can imagine, it would never scale in a large organization. That team would become bottlenecked. They would not understand how to prioritize the different projects because they don't understand the asks of marketing, sales, customer success and everythin…”
Ali Ghodsi: Databricks will be IPO ready in 2021
“We're going to be IPO ready this year and have marched towards that and are pretty far along in terms of sort of the readiness of the business everywhere.”
Databricks splits R&D into enterprise stability and new innovation teams
“All of engineering and product is separated into two different pieces. One that focuses on the things that enterprises need, large enterprises, encryption, security, authentication, stability, and so on. And another piece that focuses on these innovations.”
Ghodsi: Half of Databricks' leads come from free Community Edition
“Half of our leads comes from that.”
Ghodsi: Four major technical breakthroughs enabled the Lakehouse around 2016-2017
“Yeah, actually, the four technological breakthroughs that kind of happened at the same time, 2016, 17, at the same time, the one we contributed was Delta Lake, there was Hootie, there was Hive acid, and there was icebergs.”