Fivetran's new funding a hedge against economic uncertainty

With the economic outlook remaining unpredictable, Fivetran Inc. recently added funding as a hedge against a potential downturn.

On May 18, the vendor took on $125 million in debt financing from Vista Credit Partners. That brought its total funding to $853.1 million following a Series D venture capital funding round of $565 million in September 2021 and a Series C VC funding round of $100 million in June 2020.

Debt financing is essentially borrowing capital without giving away a stake in the company, while VC funding is the exchange of an equity stake in the company for capital.

Fivetran, founded in 2012, is a data integration specialist whose array of connectors enable organizations to move data from their many sources into databases, data warehouses and data lakes. In recent months, the vendor added a set of high-volume connectors to its data movement platform and unveiled an integration with Monte Carlo to add data observability capabilities at the point of data ingestion.

Fivetran's balance sheet, meanwhile, is strong, according to co-founder and CEO George Fraser. It includes a 50% increase in its annual revenue rate and customer roster of more than 5,000 companies. And after raising more than half a billion dollars less than two years ago, it's not in need of cash.

George Fraser

But following more than three years of economic uncertainty that began with the onset of the COVID-19 pandemic in March 2020, continued through the war in Ukraine and rising inflation, and is now threatened by a contentious battle over the United States' debt ceiling, Fraser said Fivetran wanted some certainty.

An added $125 million provides that to a certain extent, helping to ensure that the vendor can continue its research and development efforts to expand its data movement platform even if the broader economy suddenly declines.

Recently, Fraser discussed Fivetran's latest funding round, including why the vendor chose debt financing over venture capital and how the company plans to use the cash to expand its platform. In addition, he spoke about the vendor's future, which includes the goal of an initial public stock offering.

What do you hope the $125 million in new financing will enable Fivetran to do that it couldn't have done otherwise?

George Fraser: The goal of this was really about optionality, rather than any specific purpose. The macro environment continues to be really uncertain, and we don't really know how long it's going to be uncertain. Maybe inflation will get worse again and interest rates will go up further. So given the uncertainty, we just wanted to be sure that we had the flexibility to continue to operate normally and not under any circumstances be forced to do an equity raise at a time we didn't want to. It's really about maximizing flexibility, rather than having a specific plan to do "X" with the money.

Even if there are no specific projects the money is earmarked for, what can you reveal about Fivetran's roadmap and how the funding might be used to execute those plans?

Fraser: We do data movement -- that's what our product does. It takes data from here to there, which addresses a ubiquitous problem across medium and large businesses. Data movement is hideously complex. There are many data sources, and there are many destinations. Our roadmap is about perpetually trying to support all the sources people have and all the destinations people have. An example of a new source is SAP -- that's one we built relatively recently, and we're continuing to invest in it to make it possible for all types of SAP customers to use. And an example of a new destination is data lakes. That's a young destination for us that we're investing in.

Beyond new data sources and destinations for data, are there other areas of investment?

Fivetran can reliably move data in five minutes. We want to get down to one minute, and then 10 seconds.

Fraser: In addition to just the movement, you want the data to move fast. Today, Fivetran can reliably move data in five minutes. We want to get down to one minute, and then 10 seconds. There's also scale. We move some very large-scale data sets, and it's a challenge to go to the next level of scale. And then the last dimension of research and development is orchestrating transformations of the data. You move data, and then you need to transform it. We are a supporter of DBT Labs, which is an open source data transformation framework, and we have capabilities around DBT's transformation capabilities.

One other thing beyond connectors and all the engineering beneath the connectors is data governance. We're kind of like a janitor that has the keys to all the doors. But as a user, someone would like to have a map of where everything is, where everything is getting moved, where sensitive data is now and where it's going to be moved. There's a lot of complexity involved in keeping track of everything that's going on in the system, where all the paths are. You want to be able to trace data all the way through.

Does Fivetran currently provide data governance and lineage capabilities, or is that done through third-party platforms?

Fraser: There are some things we do ourselves, and then there are more things where we expose the information to third parties. There are whole companies that are just focused on this problem, so we do certain basic things and then we collect all this information about what's going on and we expose that information through APIs to our partners, who have tools built specifically for these purposes.

Hyperscalers like Microsoft have those tools.

Regarding the structure of Fivetran's new funding, why debt financing instead of VC funding?

Fraser: There are many  differences between debt financing and equity funding. But for us, at this stage, we chose debt because it's nondilutive [and does not require a company to give up equity]. Since our goal is to just increase flexibility, that's a good thing -- the cost is lower.

Since 2021, VCs have slowed their investments in tech companies -- is one of the benefits of debt financing that it avoids the difficulty of trying to attract VC interest?

Fraser: More companies are raising debt financing now. The total number might still be lower than the number raising VC funding, but the percentage for late-stage funding is higher than in the past. Debt financing is a very straightforward process because it's driven by financials. Fivetran is a reasonably large company now, and we have a lot of revenue that's high-quality, we have high margins and our existing customers tend to become larger over time, so it's a financially healthy company. That's the focus of a debt financing. It's less about future prospects to become 10 times bigger, and it's more about the quality and health of the business right now.

You used the term "late-stage funding" -- will Fivetran's next move be going public or will there be more private financing?

Fraser: We'll probably raise one more private round before we go public. That is my prediction. The plan has always been to go public, even when we were just three people.

As data volume and data complexity continue to increase, is it difficult for a company that specializes in data movement to stay on top of everything -- can you get out ahead of the expansion, or are vendors like Fivetran only able to address problems as they arise?

Fraser: It is complexity and number of sources that is the hardest part. Scale is comparatively easy. Not to say that scale is easy, but it's comparatively easy. It is whack-a-mole. There's an absolutely furious effort under way at all times behind the scenes to keep up with change and to map out all of the possible configurations of a complex data source like SAP. The good news is that there's economy of scale. Because the data movement platform is automated, every customer is running the same code. When we fix something, we only have to fix it once. When we add another rule for another configuration of SAP Hana, for example, we just have to figure it out once.

Editor's note: This Q&A has been edited for clarity and conciseness.

Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.