00:10:14 · Rajkumar Sen, Siddhartha Ahluwalia
Uh but um I'm excited to see you know uh new companies also doing a lot of things like Lake House and others. [00:10:21] S0: So, besides this speed, what was the differentiated insight in Arcion that you started with and that gave you the initial traction?
00:10:30 · Rajkumar Sen
[00:10:30] S1: See when you start a company as a first-time founder and as a solo founder, so you know the journey, right? How hard it is. So when we started, we said, you know, if you have a use case that others are not doing, Oracle is not solving, or AW is not solving, we'll solve it. It has to form within the structure of real-time data delivery. Yeah. Now the use case could be an OLTP system to an OLAP system. Now, if you think of 2018-2019, there was not a single OLAP system which was consuming events. All of them were very happy. Hey, give me a CSV file or a parquet file. Actually, if they could ingest parquet file properly in 2018, it was considered to be a big achievement. CSV was a de facto. I will not name which data warehouses are popular in 2019, 2020. You know the answer. All of them were saying we are happy with files. So, what do we do with a modern technology like ICU, right? Where we are saying, so we are looking out for use cases where event-driven transactional events meant business outcomes. Yeah. Fortunately, um, you know, one of the largest cybersecurity companies in the Bay Area, which is public now, uh, I don't know whether I can share. Uh, we met them at a conference. They were running one of the largest MongoDB clusters in the whole world. It was a uh they're cutting all the security events for all their customers. Think of like a cybersecurity company who is deployed at DoorDash, Meta, everywhere, collecting real-time security events in a uh MongoDB cluster, like 400, like huge cluster. Yeah, but what but they said hey, you know, we have a problem because when we have a breach, then we have to create a copy of that tenant for forensics, yeah. But we still have to keep collecting so that required them to also have a uh real-time replica of their MongoDB cluster with two or three seconds of latency. Yeah, and you know the PRDB use case also we're being investors similar. This is 2018-2019 time frame, and they said um when the incident happens, we want to quarantine and give snap, you know, the replica is available to the customer to do forensics. Interesting project. Of course, it's the Bay Area company with super smart engineers. Uh, MongoDB folks said we are working on a project that will give you this thing. And these set of solutions existed in Oracle and all before, right? With GoldenGate and others.
00:13:00 · Rajkumar Sen, S2, Siddhartha Ahluwalia
It's just that uh, you know, from a monolithic database like Oracle, I think they have a distributed solution now. MongoDB is a very different problem, right? Distributed database, everything, you know, you have fan out in transactions. So all the techniques that were relevant for Oracle and Sybase and IBM, you cannot do here. It's like a 400-node cluster for you have to be the replication process itself has to be distributed. Yeah. So you took on that problem. We fought a build versus buy battle for three months. [00:13:33] S2: Okay. [00:13:34] S1: Uh, I think the head of data gave us an opportunity. Said you build it, we cannot commit any money. But internal team is also building it, by the way, with the help of MongoDB. So we took that challenge and we were able to prove that you know uh we could do like uh a MongoDB replication in real time, and obviously that caught us attention with the MongoDB company. Also, we entered a good partnership with them. Uh, that was our first use case. [00:14:04] S0: That was the first customer. [00:14:05] S1: First customer, and I always tell people why invest. Hey, don't people ask me like what is your first check? You know, our first check actually was $48,000. Uh, interestingly, this in 2019. Very interesting because uh I keep hearing founders selling first check first product. [00:14:24] S0: This is 10K. You started the company in 2017.
00:14:24 · Siddhartha Ahluwalia, Rajkumar Sen, S2
[00:14:24] S0: This is 10K. You started the company in 2017. [00:14:27] S1: Yeah, 18, yeah. So I said, you know, if you bring value, yeah, I obviously the your buyer is going to want to pay you zero dollars, but you need to have the conviction and at some point say no. [00:14:40] S2: Yeah. [00:14:41] S0: Um even in Bay Area, the buyer wants to pay you zero dollars everywhere. [00:14:46] S1: Uh, because that's the nature of the buyer. I thought that is only in India. Oh no, no, no. Especially if you are a small company, yeah, it it's a very prevalent thing because you want to do escrow, you want to do this. It was a big battle for us to push back and you know, uh say this is the last thing. And how much did they initially quote? [00:15:06] S0: $10,000.
00:15:06 · Siddhartha Ahluwalia, Rajkumar Sen
[00:15:06] S0: $10,000. [00:15:08] S1: I think they said we can pay you like $10k or something. Okay, and then we started with $100. I didn't know like because you know, I I I realize that is very essential for business. Yeah, so they can't survive without you. So, but obviously we cannot charge a million or 100k because you know it's also how we have to prove it out. Yeah, you know. So we said we're gonna, this is more of a design partner, they're gonna help us build the product also. But then I don't want to stretch too thin because if I take on this customer, I'll have a couple of engineers busy and all of it. It took, it took, it took a long time with procurement. Uh no, closing took a month only, like for from right from the first day. From the first uh initiate uh conversation to closing took five and a half months. Yeah, uh, but then three months was to build the connector, and you know, we first built a um platform to move data in first infrastructure, then we started building connectors on top of it so that you know whether you build MongoDB or Cassandra doesn't matter. Uh so I always tell founders that you know if you believe that the software has value or your services a value, even if it's the first customer, do not sell for cheap. Because that sets a precedent for the next one. Yes. If you start selling for $10,000, next one can you sell for $15 because in your mind you already accepted defeat. So we had um the second customer actually at 100k. [00:16:31] S0: And who was the second customer? [00:16:33] S1: Um it was Dell. [00:16:35] S0: Okay.
00:16:35 · Siddhartha Ahluwalia, Rajkumar Sen
[00:16:35] S0: Okay. [00:16:35] S1: Yeah. So there's uh similar use case, not on MongoDB, but from a uh they wanted to do real-time replication from one of the largest warehouses uh to a modern like platform for real-time analytics. So, you know, as I said, like there is no we didn't come at a pattern because uh the pattern I actually wanted was from on-prem through all app systems. And I was trying to go to this big data warehousing company said, hey, why are you pushing files and recomputing the whole thing every day? Because the source table probably changed only one row, but you're but everybody is making money, you know. It's like if you're spinning up a big compute to redo the batch, everyone's you will make money. But uh, I think that twist came when Databricks launched Delta Lake, and then I think people are working on similar things and iceberg because Netflix was like, you know, event design is the future. Uh, and Databricks came up with a paper Delta Lake. They said no, no, no, no, no, you know, you need to do CDC into Data Warehouse, and they'd also give the opportunity to, you know, make the format open source. I think Delta Lake and Iceberg were tremendous because they launched at the same time, right? [00:17:47] S0: 2018, 2018.