Is data observability recession-proof?


Image of a young woman surrounded by computer monitors.
Image Credits: Laurence Dutton (opens in a new window) / Getty Images

Following its $135 million Series D last week, Monte Carlo became the latest unicorn in a fast-rising category: data observability, which the startup defines as “an end-to-end approach to enable teams to deliver more reliable and trustworthy data.”

If you are wondering how serious data quality issues are, Monte Carlo CEO Barr Moses has an answer: “Data quality issues still plague even the most data-driven companies. Just a few weeks ago, Unity, the popular gaming software company, cited ‘bad data’ for a $110 million impact on their ads business.”

Moses’ startup isn’t the only one to go after the data observability market opportunity. On the same day that Monte Carlo disclosed its newly minted $1.6 billion valuation, competitor Cribl confirmed its unicorn status with a new round of funding.

“While smaller than Cribl’s Series C, which came close to eclipsing $200 million, the Series D values the company at $2.5 billion post-money, according to a source. That’s up from $1.5 billion as of August 2021,” TechCrunch’s Kyle Wiggers noted.

Any three-digit deal would be noteworthy in isolation. Two of them in the same space, even more so. But what really caught our attention is that Monte Carlo’s and Cribl’s deals were announced now, right in the middle of a broad startup downturn.

We know that large rounds can take time to get both closed and disclosed, meaning that Monte Carlo’s and Cribl’s Series D rounds might reflect the state of the market a few weeks ago. But there’s a more recent data point to take into account: hiring, which is still happening.

On one side of the table, companies are still filling the kind of positions that create demand for data quality solutions. “Despite the volatility, data engineers and analytics jobs are increasing and companies are continuing to hire at record numbers for these roles,” Moses told TechCrunch. On the other, data observability startups themselves are hiring. Not just unicorns like Cribl and Monte Carlo, but also competitors like seed-funded startup Sifflet.

Could data observability be recession-proof? To find out, we talked to Moses, as well as Sifflet CEO Salma Bakouk. To complete their firsthand knowledge, we collected notes from two investors familiar with the space: FirstMark partner Matt Turck and Data Community Fund general partner Pete Soderling.

The picture that emerged from our conversations is that tailwinds for the data observability category as a whole might not translate into wins for each and every startup in the space. Why? Let’s explore.

Rising with the data tide

When we mention tailwinds for data observability, it’s because demand is driven by a broader trend. TL;DR: More and more companies are becoming data-driven, and therefore facing the kind of data quality issues that data observability startups are made to address.

Sizing a growing opportunity is never easy, but in our conversations, we heard that data obs could soon be a universal problem for large companies.

“I’m a big believer that every company, both tech and non-tech, is going to need to become not just a software company, but a data company,” Turck said. “That’s why people are excited about the opportunity — it’s a very large market and a huge trend.”

That the addressable market for data observability is large is one thing. But it would be meaningless if target companies themselves weren’t seeing reliable data as a need. According to Moses, that’s increasingly the case in all kinds of sectors.

“As companies ingest more and more data to power critical parts of the business, the opportunity for data downtime — in other words, periods of time when data is missing, unreliable, or otherwise erroneous — only grows,” Moses said. “These data-quality issues can cause organizations to lose money, waste resources and erode valuable trust with customers. In fact, Gartner estimates data downtime and poor-data quality costs the average organization $12.9 million per year, a number that’s bound to increase as businesses get more data dependent.”

In practical terms, being data dependent refers to the fact that companies are increasingly relying on sophisticated analytics and use cases driven by machine learning not just for R&D purposes, but “to power their businesses,” Soderling said. In this context, Turck noted, “being able to trust your data is not really optional anymore.”

Sailing the recession?

It’s still early to tell how demand for data, let alone data observability, will fare if the downturn were to turn into a full-blown recession. Data observability, Soderling said, “is clearly already a priority for data-driven companies.” But, he added “I think we’ll see in this current downturn which companies are really prepared to put their money where their mouth is when it comes to being truly data driven versus data curious.”

In other words, the downturn could temporarily reduce the total addressable market of data observability startups. However, it may also make it easier to preach to the converted. Sifflet, for instance, reports seeing “more customer demand than ever before in the past couple of months.”

As to why demand is increasing, Bakouk ventured that companies want the kind of difficult decisions they need to make right now to be backed by reliable data. As exemplified by Unity, the market is also less forgetting during times of uncertainty, she noted. “Data incidents, or what I call data catastrophes, are simply not tolerated.”

But even if demand for data observability holds up or increases, startups in the space might still be affected by the downturn. More precisely, they could pay the price of past euphoria.

“As the opportunity is both very large and fairly obvious, a number of startups were launched in a matter of a couple of years to go after it,” Turck said. “And that coincided with a very hot funding market, both in general but also in the data infrastructure space, as many VCs got really excited after the amazing success of Snowflake. As a result, you end up in this situation where you have a lot of smart founders running startups that are promising and well funded, but everyone is pretty early in their journey and the category is already very crowded.

“It’s unclear how it all shakes out,” Turck added.

We tend to agree, but let’s still look at what we know so far.

Don’t crown winners yet

One of the things we know is that Monte Carlo just raised a massive Series D round (and so did Cribl.) When asked how to interpret this, sources shared mixed impressions.

Bakouk described Monte Carlo’s announcement as “a great signal for the category as a whole” and a “great proof of the category’s legitimacy.” It could help further educate customers who, “although well aware of the consequences of bad data, are still unsure of what to expect from a tool let alone the budget that should be allocated to it.”

However, Monte Carlo’s new unicorn status doesn’t necessarily reflect a new wave of enthusiasm for data observability startups. “The Monte Carlo funding is more a trailing indicator than a leading indicator of excitement about the space, in my opinion,” Turck said.

Turck has another hypothesis on Monte Carlo’s fundraising record. “The fact that Monte Carlo has basically raised four back-to-back rounds in less than two years,” he told TechCrunch, “is also a bit of a ‘shock and awe’ strategy from both the founders and the VCs to will into existence the category-dominating platform that covers all parts of the [data-quality] problem.”

Mega-rounds like Monte Carlo can act as a deterrent rather than an incentive. “That kind of strategy can have the side effect of discouraging others from entering, or further funding, the space,” Turck said. Either way, he doesn’t expect as many new players as a couple of years ago: “As the financing market cools down, I don’t anticipate a lot more brand new entrants, unless they offer something truly differentiated.”

How about existing players? Again, feelings are mixed. “Funding will certainly become trickier, but great ideas with solid metrics will continue to get funded,” Bakouk said. Even if they have funding, they should still be wary of spending cash as if market conditions hadn’t changed. “I think all startups with high valuations compared to their actual revenues (like Monte Carlo) should be cautious heading into the current market downtrend,” Soderling warned.

More than its spending plans, Monte Carlo’s fundraising strategy seems to reflect the company’s vision for a space that its co-founders have compared again and again to another one: software observability. “Just like every engineering team leverages a reliability solution like Datadog or New Relic, every data team needs an observability solution to ensure their data products are trusted and accurate,” Moses argued.

As Alex Wilhelm noted, “the analogy [between data observability and software observability] is reasonable as both software niches deal with flagging issues with software systems in motion, if somewhat rosy for Monte Carlo.” Indeed, both New Relic and Datadog, well-known software observability tools, are public companies.

If data observability is anything like application performance monitoring, then it may not be a winner-take-all market. The APM market, Soderling noted, has “several large players: Datadog, New Relic, AppDynamics, etc.”

Oligopoly then, not monopoly. But that still leaves room for consolidation, something that is due to data observability having a lot in common with adjacent categories. “Right now, you have a bunch of startups tackling different parts of the problem: lineage, data quality, observability per se, orchestration, etc. But ultimately customers just want their business problems fixed: Is my data reliable? If not, what’s the problem? And once I know the problem, how do I fix it?”

Turck is well placed to talk about consolidation. He participated in the most recent funding round of data orchestration startup Astronomer, which recently acquired data lineage Datakin, in which he was the lead investor. As for Soderling, he invested in Anomalo, Soda and Superconductive, which strictly speaking aren’t data observability startups but could be seen as competitors to Monte Carlo and its closest peers. These include Sifflet, but also Acceldata, Datafold and Metaplane.

Bakouk too wouldn’t be surprised to see more concentration. “I think there will be consolidation with data lineage, data catalogs, which will be useful for the data management category.” She hopes her startup is one step ahead; Sifflet invested in building its own data lineage solution and describes itself as a full data stack observability platform. “We monitor the data across the whole enterprise data pipeline to ensure its reliability from source to destination,” she said.

Moses also describes Monte Carlo’s vision as encompassing. “We believe that the winning approach will apply an end-to-end lens across the entire data stack, providing not just a point solution for the data warehouse or BI layer, but a comprehensive platform that gives data teams the tools to detect, resolve and prevent data issues at each stage of the pipeline — no matter what stack they’re using.”

Extrapolating from Turck’s comments, going broad seems to be a good bet. “Some sophisticated customers will want to stitch best-of-breed solutions together, but many (most?) will want a broad platform that takes care of all parts of the problem in a cohesive, integrated manner,” he said.

The APM analogy once again came in handy. “If you look at Datadog as a comparison,” Turck said, “they’re a broad horizontal platform that takes care of everything. I think that’s what people are going to want in the data space, too.”

Therefore, “it’s not hard to imagine how a very big public company could be built in the data infrastructure space, as that market continues to grow exponentially over the next few years.”

Who could that be, if anyone? Only time will tell.

Disclosure: I am a former contractor of Pete Soderling’s Data Council. I don’t have ties of any kind to his fund or portfolio companies.

More TechCrunch

Founder-market fit is one of the most crucial factors in a startup’s success, and operators (someone involved in the day-to-day operations of a startup) turned founders have an almost unfair advantage…

OpenseedVC, which backs operators in Africa and Europe starting their companies, reaches first close of $10M fund

A Singapore High Court has effectively approved Pine Labs’ request to shift its operations to India.

Pine Labs gets Singapore court approval to shift base to India

The AI Safety Institute, a U.K. body that aims to assess and address risks in AI platforms, has said it will open a second location in San Francisco. 

UK opens office in San Francisco to tackle AI risk

Companies are always looking for an edge, and searching for ways to encourage their employees to innovate. One way to do that is by running an internal hackathon around a…

Why companies are turning to internal hackathons

Featured Article

I’m rooting for Melinda French Gates to fix tech’s broken ‘brilliant jerk’ culture

Women in tech still face a shocking level of mistreatment at work. Melinda French Gates is one of the few working to change that.

16 hours ago
I’m rooting for Melinda French Gates to fix tech’s  broken ‘brilliant jerk’ culture

Blue Origin has successfully completed its NS-25 mission, resuming crewed flights for the first time in nearly two years. The mission brought six tourist crew members to the edge of…

Blue Origin successfully launches its first crewed mission since 2022

Creative Artists Agency (CAA), one of the top entertainment and sports talent agencies, is hoping to be at the forefront of AI protection services for celebrities in Hollywood. With many…

Hollywood agency CAA aims to help stars manage their own AI likenesses

Expedia says Rathi Murthy and Sreenivas Rachamadugu, respectively its CTO and senior vice president of core services product & engineering, are no longer employed at the travel booking company. In…

Expedia says two execs dismissed after ‘violation of company policy’

Welcome back to TechCrunch’s Week in Review. This week had two major events from OpenAI and Google. OpenAI’s spring update event saw the reveal of its new model, GPT-4o, which…

OpenAI and Google lay out their competing AI visions

When Jeffrey Wang posted to X asking if anyone wanted to go in on an order of fancy-but-affordable office nap pods, he didn’t expect the post to go viral.

With AI startups booming, nap pods and Silicon Valley hustle culture are back

OpenAI’s Superalignment team, responsible for developing ways to govern and steer “superintelligent” AI systems, was promised 20% of the company’s compute resources, according to a person from that team. But…

OpenAI created a team to control ‘superintelligent’ AI — then let it wither, source says

A new crop of early-stage startups — along with some recent VC investments — illustrates a niche emerging in the autonomous vehicle technology sector. Unlike the companies bringing robotaxis to…

VCs and the military are fueling self-driving startups that don’t need roads

When the founders of Sagetap, Sahil Khanna and Kevin Hughes, started working at early-stage enterprise software startups, they were surprised to find that the companies they worked at were trying…

Deal Dive: Sagetap looks to bring enterprise software sales into the 21st century

Keeping up with an industry as fast-moving as AI is a tall order. So until an AI can do it for you, here’s a handy roundup of recent stories in the world…

This Week in AI: OpenAI moves away from safety

After Apple loosened its App Store guidelines to permit game emulators, the retro game emulator Delta — an app 10 years in the making — hit the top of the…

Adobe comes after indie game emulator Delta for copying its logo

Meta is once again taking on its competitors by developing a feature that borrows concepts from others — in this case, BeReal and Snapchat. The company is developing a feature…

Meta’s latest experiment borrows from BeReal’s and Snapchat’s core ideas

Welcome to Startups Weekly! We’ve been drowning in AI news this week, with Google’s I/O setting the pace. And Elon Musk rages against the machine.

Startups Weekly: It’s the dawning of the age of AI — plus,  Musk is raging against the machine

IndieBio’s Bay Area incubator is about to debut its 15th cohort of biotech startups. We took special note of a few, which were making some major, bordering on ludicrous, claims…

IndieBio’s SF incubator lineup is making some wild biotech promises

YouTube TV has announced that its multiview feature for watching four streams at once is now available on Android phones and tablets. The Android launch comes two months after YouTube…

YouTube TV’s ‘multiview’ feature is now available on Android phones and tablets

Featured Article

Two Santa Cruz students uncover security bug that could let millions do their laundry for free

CSC ServiceWorks provides laundry machines to thousands of residential homes and universities, but the company ignored requests to fix a security bug.

3 days ago
Two Santa Cruz students uncover security bug that could let millions do their laundry for free

TechCrunch Disrupt 2024 is just around the corner, and the buzz is palpable. But what if we told you there’s a chance for you to not just attend, but also…

Harness the TechCrunch Effect: Host a Side Event at Disrupt 2024

Decks are all about telling a compelling story and Goodcarbon does a good job on that front. But there’s important information missing too.

Pitch Deck Teardown: Goodcarbon’s $5.5M seed deck

Slack is making it difficult for its customers if they want the company to stop using its data for model training.

Slack under attack over sneaky AI training policy

A Texas-based company that provides health insurance and benefit plans disclosed a data breach affecting almost 2.5 million people, some of whom had their Social Security number stolen. WebTPA said…

Healthcare company WebTPA discloses breach affecting 2.5 million people

Featured Article

Microsoft dodges UK antitrust scrutiny over its Mistral AI stake

Microsoft won’t be facing antitrust scrutiny in the U.K. over its recent investment into French AI startup Mistral AI.

3 days ago
Microsoft dodges UK antitrust scrutiny over its Mistral AI stake

Ember has partnered with HSBC in the U.K. so that the bank’s business customers can access Ember’s services from their online accounts.

Embedded finance is still trendy as accounting automation startup Ember partners with HSBC UK

Kudos uses AI to figure out consumer spending habits so it can then provide more personalized financial advice, like maximizing rewards and utilizing credit effectively.

Kudos lands $10M for an AI smart wallet that picks the best credit card for purchases

The EU’s warning comes after Microsoft failed to respond to a legally binding request for information that focused on its generative AI tools.

EU warns Microsoft it could be fined billions over missing GenAI risk info

The prospects for troubled banking-as-a-service startup Synapse have gone from bad to worse this week after a United States Trustee filed an emergency motion on Wednesday.  The trustee is asking…

A US Trustee wants troubled fintech Synapse to be liquidated via Chapter 7 bankruptcy, cites ‘gross mismanagement’

U.K.-based Seraphim Space is spinning up its 13th accelerator program, with nine participating companies working on a range of tech from propulsion to in-space manufacturing and space situational awareness. The…

Seraphim’s latest space accelerator welcomes nine companies