00:40:30 · Siddhartha Ahluwalia, Rajkumar Sen
[00:40:30] S0: Yeah, because cloud today combined AWS are at between 180 and 190 billion, uh Azure is at 140 billion, they run rates, uh, 140 billion run rate, and GCP is at 90 to 100 billion. So combined if you see 180 plus 140, the other 500 billion. [00:40:46] S1: No, no, totally true. And see, I think all this valuation is also valuation, these are the revenue. Yeah, revenue. Yeah, no, I'm seeing the like the rev. Sorry, the the revenue also this is like an app ecosystem, right? You had Aurora and all the databases and data management. All of them will like start. They you're not going to charge premium for databases right now. It's like an operating system right now. You will charge on the hardware and maybe some premium. Where you are, the money people will pay is on AI services. Innovation will happen in the database space, but it will be one you know table stack feature where you can't get a new customer by just building a new database. So given that the top dollars will be because that's net new thing, right? Yeah, databases are awesome, but um, can you deploy a new AI application which is like doing some something new for you just by using a new database? No, you know, you need to have all the inferencing and all of it. So yeah, I'm very excited. Uh, I actually started looking at, you know, so you know, uh, some uh as just as an academic in me, you know, I look at that very interesting.
00:40:46 · Rajkumar Sen, Siddhartha Ahluwalia
[00:40:46] S1: No, no, totally true. And see, I think all this valuation is also valuation, these are the revenue. Yeah, revenue. Yeah, no, I'm seeing the like the rev. Sorry, the the revenue also this is like an app ecosystem, right? You had Aurora and all the databases and data management. All of them will like start. They you're not going to charge premium for databases right now. It's like an operating system right now. You will charge on the hardware and maybe some premium. Where you are, the money people will pay is on AI services. Innovation will happen in the database space, but it will be one you know table stack feature where you can't get a new customer by just building a new database. So given that the top dollars will be because that's net new thing, right? Yeah, databases are awesome, but um, can you deploy a new AI application which is like doing some something new for you just by using a new database? No, you know, you need to have all the inferencing and all of it. So yeah, I'm very excited. Uh, I actually started looking at, you know, so you know, uh, some uh as just as an academic in me, you know, I look at that very interesting. [00:41:58] S0: Um, let's see, you have now been inside Databricks, partnered with Databricks, you know, Ali closely, you know, inside what makes Databricks so successful? Because for a long period of time, uh, you know, they were nobody for the first five, six years.
00:42:14 · Rajkumar Sen
[00:42:14] S1: I think it's a little bit uh unfair. Uh I think revenue-wise, they were behind others. Uh see, where I used to work for MemSQL, we were partners with Databricks. First, I got a chance to meet Ali and Glenel and others. Revenue of Database less than MemSQL. But see, I think judging a company on revenue is like this for the pattern matching, like, and I always tell my VC friends, like, you know, look at the potential, yeah, look at the innovative streak, uh, because you know, it's not one product, right? I think I think I felt that one see I didn't work at other companies, so it's very hard for me to judge. But um I feel like starting with Ali and Reynold and Patrick and even the whole executive team, there is a relentless push to achieve more. I know everybody talks about it, but then that company is actually true. Um and there is always like a push to do new products, and if you see like Databricks wants to do everything, which is actually good. Yeah, it could mean bad news for some startups who want to do a few things, uh, including maybe I start a company, but it's always good to have them validate. So if you're starting a company in a space which they are also building, it's actually good that you know that you know it's valuable. Why would they be there? Um, but the I think there's a lot of founder driven technical like push. Uh, because you know, you look at Ali, he's probably working 20 hours a day, you are also motivated to, you know, do things, right? Yeah. Also, I think a lot of people have spoken about Ali. I will also mention today that I think he's truly very unique. I actually haven't seen anybody who has that much technical and business depth.
00:44:19 · S2
[00:44:19] S2: Okay.
00:44:19 · Rajkumar Sen
[00:44:19] S1: Maybe Larry Ellison at Oracle was that person, or maybe Thomas Kurian. I actually have, and I don't know what the hardware says, maybe Jensen obviously has that. Satya Nadella and these people are great, but I'm talking about from the enterprise segment. When I was at Oracle, I saw that Larry and Thomas, maybe more Larry, had the technical depth as well as the business depth. Understanding of the technology as a product manager, also knowing how to talk to customers. And I think Ali is even better. He has knowledge about each and every product of Databricks, each and every product of competitors, and he knows the engineers, and he can understand. Like you spent 15 minutes with him on a technical problem, totally different. He can understand the nuances around it. But then he can take the same technical thing and can also talk to customers and can convince customers about it. If you have a CEO that's unique, and you know, I mean Reynold and others are also like extremely like you know motivated and super sharp people, they can hire also good people. And that combination is lethal. Um and uh the other thing I've seen at Databricks is they're very quick to understand the trends. 2023 summers, they are like, okay, people are going to need AI infrastructure in the next three years. So we're going to buy Mosaic for 1 billion. A lot of people are like, oh, 1 billion for mosaic. Look at it now. People are using Databricks as a compute machinery for AI more than AWS. They're not just using Databricks. So if Ali wouldn't have bought Mosaic in 2023, this would not have been possible. Uh Arcion was a you know tremendously to be ahead, like you know, connecting you know uh data in real time. Like obviously, we are partners with Fivetran and others, but you need to have your own solution for internal, you know, for the use cases you want to do better. Now it's getting into your genie. So there is always that vision and then tabular, right? Uh uh they could have said, you know, we're gonna protect Delta Lake and Iceberg can be somewhere else, but they want to merge the whole technologies together. So I think that you need to have that technical death, um, custom, you know, the business vision, but also like forward thinking. What people need after two, three years. I think uh Ali Rand like the whole founding today, we create.
00:46:52 · Rajkumar Sen, S2, Siddhartha Ahluwalia
I'm sure like they're also thinking now, like, you know, what it's very hard to, I don't know. Yeah, every acquisition of Databricks that is looked to be oh my god, they spent so much money and all of it. After three years, you'll be like, oh, okay, okay, okay. You know what? This actually makes sense, it was very cheap. Um because uh even in MosaicML, I think the revenue was hardly 10 million when Ali acquired it for uh I don't think database acquires uh company for revenue, they acquire it for the talent team and what they can bring for the potential. That is vision. There are very few companies like that. I think there's only one company right now that thinks like that. Uh, I made to see another company uh where all the acquisitions are driven by vision. [00:47:42] S2: Yeah. [00:47:43] S1: Uh maybe open air, maybe open air acquired a few companies. [00:47:47] S0: Anthropic, maybe, but nothing became a big product inside exactly with Databricks.