Why Machbase’s CEO Started Teaching Customers: PMF and Gartner
Andrew Sungjin Kim, CEO of Machbase
Ten Years Have Already Passed
It has been ten years since I founded Machbase. After spending many years developing in-memory database engines, I became fascinated by the big-data era and convinced that “machine data,” as we called it in 2013, would eventually outnumber ordinary transaction data.
Back in 2013, Splunk and similar products were gaining momentum for log data, while Hadoop was attracting enormous attention for unstructured data such as text files, images, and video. Amid that excitement, I held onto a somewhat hazy belief that a new kind of fast database would eventually be needed.
And Yet…
Do you remember the article in our previous newsletter, “A Proposal for Korea’s Public Procurement Market: The Era of Time-Series Databases Is Approaching”? Although it was framed as a proposal for the public sector, its underlying message was this:
“I had been working on time-series databases for years before broader awareness began to emerge around 2019. By 2023, roughly a decade after we started, the category had established itself in the United States. In Korea, however, we were only beginning.” A rather sobering realization.
Gartner’s 2023 report presents the state of time-series databases as shown above.
But Here Is the Problem
My experience in Korea does not seem to match that picture. Reading Gartner’s analysis, I would expect a substantial share of relevant IT professionals—perhaps 30–50% by 2024—to know what we do or at least to have heard about it. In practice, my personal impression is that only about 2–5% of the people I meet recognize the need for, or even the existence of, time-series databases.
That is where my concern begins.
If industrial, IoT, and other machine-generated data really is growing at the explosive rate of 61% a year cited in the IDC figures I was referring to, and if so many practitioners struggle with data processing, why is awareness and adoption developing so much more slowly than I imagined?
Have You Heard of PMF?
PMF stands for product-market fit. Put simply, it means finding the market that truly needs your product.
The term is deeply embedded in the US startup and venture-investment world. With only a little exaggeration, one could say that a startup’s entire journey is a search for PMF.
Across the universities, venture-capital firms, accelerators, and incubators in the San Francisco Bay Area, a great many programs, seminars, and talks about business success eventually lead to that same destination: finding PMF.
Two years before writing this, I joined a Stanford program for founders and aspiring entrepreneurs from around the world. It covered the journey from product planning and development to pitching and fundraising. For various reasons, I did not finish it.
PMF was the term I heard most often. One of the program’s promises was, essentially, “We will show you how to find it.”
One memorable expression stayed with me: finding PMF would produce a customer response as unmistakable and explosive as stepping on a landmine.
A Wake-Up Call
A few days ago, I came across an article that felt like a blow to the head—in the best possible sense. The venture-capital firm Sequoia had published “The Arc Product-Market Fit Framework.”
The framework distinguishes three broad patterns of PMF.
The first is “Hair on Fire”: solving a problem so urgent that customers feel as though their hair is burning. Products in this category can grow quickly by rapidly relieving an unmistakable pain.
The second is “Hard Fact”: the market has a real problem, but customers have come to accept it as an unavoidable part of life. This, too, can be fertile ground for PMF.
The third is “Future Vision”: a radically new product creates demand for something customers have not yet imagined.
Why did this article have such an impact on me?
Because I had spent the past ten years searching for PMF, continually asking where we stood—and here was an example of a company that found it in circumstances that felt remarkably familiar.
Which Company?
As described above, the Hard Fact category involves pain so widespread and familiar that people no longer treat it as a problem to solve.
One company that found PMF in that setting was HubSpot, known for its work in inbound and email marketing.
When HubSpot was founded in the mid-2000s, many businesses relied heavily on advertising, direct mail, and telephone outreach. Despite high costs and limited effectiveness, these slow, inefficient methods remained widely accepted.
HubSpot promoted an internet-based approach built around SEO, content, and email marketing, offering a much more efficient way to reach customers. There was the opportunity for PMF.
The crucial point, however, is that the underlying ideas were not exclusive to HubSpot. Others could have thought of them and put them into practice.
So how did HubSpot turn that opportunity into widespread adoption?
By writing a book that organized those ideas—and using education to help customers put them to work.
That realization delivered another powerful jolt.
In a Hard Fact market, new technology and products alone may not be enough to change established habits. HubSpot showed the importance of continually teaching customers a more effective approach and demonstrating how to make it work. Education and proof were central to the change.
Eureka
I brought my thoughts back to Machbase. What should I do next?
I began by writing down a few observations.
Data volumes are growing and will continue to grow.
Customers are already experiencing problems caused by that growth.
But those problems have been with them so long that they have become familiar habits.
Then I outlined how we might help change the market.
Technologies and products exist that can solve these data problems.
We need to organize the knowledge and information into clear, structured material.
We must share that material, teach customers how to use it, and demonstrate that it solves their problems.
As more customers adopt the new approach, the market could change at an accelerating pace.
That was the path my thinking took.
So I Decided to Meet Customers and Teach Regularly
If you saw our training announcements from the month before this article, you may have noticed that the CEO and CTO were teaching the sessions themselves. Yes, we have plenty of other work to do. We had actually started before learning about HubSpot’s story, but the connection now made sense.
Our excellent colleagues had already been delivering training. Still, I thought there was something valuable about having the people who built Machbase explain the product and its technology directly to customers. Who better to communicate what we were trying to achieve?
So, as I write this, I am updating the training materials, debating the curriculum with our CTO, and preparing the next sessions. I am also considering a well-designed book about Machbase Neo that we could give to participants.
Just as HubSpot did.
Improving the Next Training Session
In the morning, I will focus on the concepts and the overall role of time-series databases. In the afternoon, our CTO, who leads Neo engine development, will teach a developer-oriented session with more demonstrations of practical use cases, followed by a short hands-on exercise.
As previously announced, the Machbase Academy Center also provides regular-training materials and online lessons for self-study. Please make use of them whenever they are helpful.
Closing Thoughts
This has become a longer story than I intended. I hope it offers something useful to the many startup founders and team members wrestling with questions similar to mine.
Who knows?
Perhaps one day I will experience that unmistakably explosive customer response myself.
Thank you!
