The Ledger
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why aren't all 13 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
Stancil: Native SaaS warehouse connections could undercut Fivetran's core revenue
“You know, it doesn't undercut everything for Fivetran, but it potentially undercuts the big sources, which I imagine are the things that are, like, the real drivers of revenue for them.”
Fraser: Fivetran succeeded by guaranteeing data accuracy instead of selling toolkits
“And the really critical thing we did that laid the foundation for our eventual success was that we said that it was our responsibility to make the data match. Which is actually unusual in the field of data integration. Most data integration tools, they see the…”
Handy: Cloud platforms care about compute consumption, not partner revenue
“My read is that people like us, people like Fivetran, while we are critical to their success as platforms, because we drive a ton of consumption. They don't actually really care about the dollars that we make as businesses. Cause they're so tiny relative to th…”
Handy: The core modern data stack architecture remains a good idea
“When people started using the term modern data stack, there was a there, like fivetran, dbt, mode, looker, et cetera. These are tools that. Were built around an idea of how data technology should work. And it was a, it was, and is a good idea.”
Fraser: Post-load master data management in the warehouse is safely non-destructive
“And this is different than how it's historically been done, but the big advantage of Doing MDM and other similar things in this way is that it's non-destructive. So you still have the original data. If you make a mistake and you realize later, oh, I said these…”
Handy: dbt Labs and Fivetran are not going anywhere
“And so that means that companies like us and companies like Fivetran that are big parts of that, you know, we're not going anywhere.”
Fraser: In-warehouse transformation compute is cheaper than data engineering time
“The additional cost of compute and storage to replicate the extra data, to do those steps, those transformation steps inside the warehouse Are so small now, you know, they're less than what it's going to cost you to pay your data engineer for a week to build y…”
Fraser: Building custom data pipelines works best for large, stable internal sources
“If the data source is really large, it's something that's just yours, so Fivetran's never going to build a connector to it, and it's relatively stable, like it's not constantly changing configuration, then you can build your own data pipeline using the tools p…”
Fraser: SaaS vendors sometimes alter their APIs specifically for Fivetran
“And then sometimes they actually change the APIs for us.”
Fraser: Fivetran has customers running billing out of their data warehouse
“We have customers who run billing out of their data warehouse.”
Turck: Fivetran generates over $100M in annual revenue
“And is actually as far as I know, one of those, like, companies are over a hundred million in, in, in revenue.”
Fraser: Marketing data is often Fivetran's initial enterprise use case
“So marketing data is often like the initial use case for Fivetran at a large company.”
Fraser: Fivetran is publishing standards for replication-friendly API design
“And we're working on we're working on publishing more about, like, what do you need to do to make an API that's friendly to replication for data warehousing? Whether it's by us or one of our competitors or just the customers building their own data pipelines, …”