Tag Archives: open source

Mirantis launches cloud-native data center-as-a-service software

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Mirantis has been around the block, starting way back as an OpenStack startup, but a few years ago the company began to embrace cloud-native development technologies like containers, microservices and Kubernetes. Today, it announced Mirantis Flow, a fully managed open source set of services designed to help companies manage a cloud-native data center environment, whether your infrastructure lives on-prem or in a public cloud.

“We’re about delivering to customers an open source-based cloud-to-cloud experience in the data center, on the edge, and interoperable with public clouds,” Adrian Ionel, CEO and co-founder at Mirantis explained.

He points out that the biggest companies in the world, the hyperscalers like Facebook, Netflix and Apple, have all figured out how to manage in a hybrid cloud-native world, but most companies lack the resources of these large organizations. Mirantis Flow is aimed at putting these same types of capabilities that the big companies have inside these more modest organizations.

While the large infrastructure cloud vendors like Amazon, Microsoft and Google have been designed to help with this very problem, Ionel says that these tend to be less open and more proprietary. That can lead to lock-in, which today’s large organizations are looking desperately to avoid.

“[The large infrastructure vendors] will lock you into their stack and their APIs. They’re not based on open source standards or technology, so you are locked in your single source, and most large enterprises today are pursuing a multi-cloud strategy. They want infrastructure flexibility,” he said. He added, “The idea here is to provide a completely open and flexible zero lock-in alternative to the [big infrastructure providers, but with the] same cloud experience and same pace of innovation.”

On balance, the cloud has been a huge boon to startups

They do this by putting together a stack of open source solutions in a single service. “We provide virtualization on top as part of the same fabric. We also provide software-defined networking, software-defined storage and CI/CD technology with DevOps as a service on top of it, which enables companies to automate the entire software development pipeline,” he said.

As the company describes the service in a blog post published today, it includes “Mirantis Container Cloud, Mirantis OpenStack and Mirantis Kubernetes Engine, all workloads are available for migration to cloud native infrastructure, whether they are traditional virtual machine workloads or containerized workloads.”

For companies worried about migrating their VMware virtual machines to this solution, Ionel says they have been able to move these VMs to the Mirantis solution in early customers. “This is a very, very simple conversion of the virtual machine from VMware standard to an open standard, and there is no reason why any application and any workload should not run on this infrastructure — and we’ve seen it over and over again in many many customers. So we don’t see any bottlenecks whatsoever for people to move right away,” he said.

It’s important to note that this solution does not include hardware. It’s about bringing your own hardware infrastructure, either physical or as a service, or using a Mirantis partner like Equinix. The service is available now for $15,000 per month or $180,000 annually, which includes: 1,000 core/vCPU licenses for access to all products in the Mirantis software suite plus support for 20 virtual machine (VM) migrations or application onboarding and unlimited 24×7 support. The company does not charge any additional fees for control plane and management software licenses.


By Ron Miller

Explosion snags $6M on $120M valuation to expand machine learning platform

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Explosion, a company that has combined an open source machine learning library with a set of commercial developer tools, announced a $6 million Series A today on a $120 million valuation. The round was led by SignalFire, and the company reported that today’s investment represents 5% of its value.

Oana Olteanu from SignalFire will be joining the board under the terms of the deal, which includes warrants of $12 million in additional investment at the same price.

“Fundamentally, Explosion is a software company and we build developer tools for AI and machine learning and natural language processing. So our goal is to make developers more productive and more focused on their natural language processing, so basically understanding large volumes of text, and training machine learning models to help with that and automate some processes,” company co-founder and CEO Ines Montani told me.

The company started in 2016 when Montani met her co-founder, Matthew Honnibal in Berlin where he was working on the spaCy open source machine learning library. Since then, that open source project has been downloaded over 40 million times.

In 2017, they added Prodigy, a commercial product for generating data for the machine learning model. “Machine learning is code plus data, so to really get the most out of the technologies you almost always want to train your models and build custom systems because what’s really most valuable are problems that are super specific to you and your business and what you’re trying to find out, and so we saw that the area of creating training data, training these machine learning models, was something that people didn’t pay very much attention to at all,” she said.

The next step is a product called Prodigy Teams, which is a big reason the company is taking on this investment. “Prodigy Teams  is [a hosted service that] adds user management and collaboration features to Prodigy, and you can run it in the cloud without compromising on what people love most about Prodigy, which is the data privacy, so no data ever needs to get seen by our servers,” she said. They do this by letting the data sit on the customer’s private cluster in a private cloud, and then use Prodigy Team’s management features in the public cloud service.

Today, they have 500 companies using Prodigy including Microsoft and Bayer in addition to the huge community of millions of open source users. They’ve built all this with just 6 early employees, a number that has grown to 17 recently and they hope to reach 20 by year’s end.

She believes if you’re thinking too much about diversity in your hiring process, you probably have a problem already. “If you go into hiring and you’re thinking like, oh, how can I make sure that the way I’m hiring is diverse, I think that already shows that there’s maybe a problem,” she said.

“If you have a company, and it’s 50 dudes in their 20s, it’s not surprising that you might have problems attracting people who are not white dudes in their 20s. But in our case, our strategy is to hire good people and good people are often very diverse people, and again if you play by the [startup] playbook, you could be limited in a lot of other ways.”

She said that they have never seen themselves as a traditional startup following some conventional playbook. “We didn’t raise any investment money [until now]. We grew the team organically, and we focused on being profitable and independent [before we got outside investment],” she said.

But more than the money, Montani says that they needed to find an investor that would understand and support the open source side of the business, even while they got capital to expand all parts of the company. “Open source is a community of users, customers and employees. They are real people, and [they are not] pawns in [some] startup game, and it’s not a game. It’s real, and these are real people,” she said.

“They deserve more than just my eyeballs and grand promises. […] And so it’s very important that even if we’re selling a small stake in our company for some capital [to build our next] product [that open source remains at] the core of our company and that’s something we don’t want to compromise on,” Montani said.

Companies betting on data must value people as much as AI


By Ron Miller

Would the math work if Databricks were valued at $38B?

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Databricks, the open-source data lake and data management powerhouse has been on quite a financial run lately. Today Bloomberg reported the company could be raising a new round worth at least $1.5 billion at an otherworldly $38 billion valuation. That price tag is up $10 billion from its last fundraise in February when it snagged $1 billion at a $28 billion valuation.

Databricks declined to comment on the Bloomberg post and its possible new valuation.

The company has been growing like gangbusters, giving credence to the investor thesis that the more your startup makes, the more it is likely to make. Consider that Databricks closed 2020 with $425 million in annual recurring revenue, which in itself was up 75% from the previous year.

As revenue goes up so does valuation, and Databricks is a great example of that rule in action. In October 2019, the company raised $400 million at a seemingly modest $6.2 billion valuation (if a valuation like that can be called modest). By February 2021, that had ballooned to $28 billion, and today it could be up to $38 billion if that rumor turns out to be true.

Databricks raises $1B at $28B valuation as it reaches $425M ARR

One of the reasons that Databricks is doing so well is it operates on a consumption model. The more data you move through the Databricks product family, the more money it makes, and with data exploding, it’s doing quite well, thank you very much.

It’s worth noting that Databricks’s primary competitor, Snowflake went public last year and has a market cap of almost $83 billion. In that context, the new figure doesn’t feel quite so outrageous, But what does it mean in terms of revenue to warrant a valuation like that. Let’s find out.

Valuation math

Let’s rewind the clock and observe the company’s recent valuation marks and various revenue results at different points in time:

  • Q3 2019: $200 million run rate, $6.2 billion valuation
  • Q3 2020: $350 million run rate, no known valuation change
  • EoY 2020: $425 million run rate, $28 billion valuation (Q1 valuation)
  • Q3 2021: Unclear run rate, possible $38 billion valuation

The company’s 2019 venture round gave Databricks a 31x run rate multiple. By the first quarter of 2021, that had swelled to a roughly 66x multiple if we compare its final 2020 revenue pace to its then-fresh valuation. Certainly software multiples were higher at the start of 2021 than they were in late 2019, but Databricks’s $28 billion valuation was still more than impressive; investors were betting on the company like it was going to be a key breakout winner, and a technology company that would go public eventually in a big way.

To see the company possibly raise more funds would therefore not be surprising. Presumably the company has had a good few quarters since its last round, given its history of revenue accretion. And there’s only more money available today for growing software companies than before.

But what to make of the $38 billion figure? If Databricks merely held onto its early 2021 run rate multiple, the company would need to have reached a roughly $575 million run rate, give or take. That would work out to around 36% growth in the last two-and-a-bit quarters. That works out to less than $75 million in new run rate per quarter since the end of 2020.

Is that possible? Yeah. The company added $75 million in run rate between Q3 2020 and the end of the year. So you can back-of-the-envelope the company’s growth to make a $38 billion valuation somewhat reasonable at a flat multiple. (There’s some fuzz in all of our numbers, as we are discussing rough timelines from the company; we’ll be able to go back and do more precise math once we get the Databricks S-1 filing in due time.)

Databricks co-founder and CEO Ali Ghodsi is coming to TC Sessions: SaaS

All this raises the question of whether Databricks should be able to command such a high multiple. There’s some precedent. Recently, public software company Monday.com has a run rate multiple north of 50x, for example. It earned that mark on the back of a strong first quarter as a public company.

Databricks securing a higher multiple while private is not crazy, though we wonder if the data-focused company is managing a similar growth rate. Monday.com grew 94% on a year-over-year basis in its most recent quarter.

All this is to say that you can make the math shake out for Databricks to raise at a $38 billion valuation, but built into that price is quite a lot of anticipated growth. Top quartile public software companies today trade for around 23x their forward revenues, and around 27x their present-day revenues, per Bessemer. To defend its possible new valuation when public, then, leaves quite a lot of work ahead of Databricks.

The company’s CEO, Ali Ghodsi, will join us at TC Sessions: SaaS on October 27th, and we should know by then if this rumor is, indeed true. Either way, you can be sure we are going to ask him about it.

Why one Databricks investor thinks the company may be undervalued

 


By Ron Miller

With buyout, Cloudera hunts for relevance in a changing market

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When Cloudera announced its sale to a pair of private equity firms yesterday for $5.3 billion, along with a couple of acquisitions of its own, the company detailed a new path that could help it drive back towards relevance in the big data market.

When the company launched in 2008, Hadoop was in its early days. The open source project developed at Yahoo three years earlier was built to deal with the large amounts of data that the Internet pioneer generated. It became increasingly clear over time that every company would have to deal with growing data stores, and it seemed that Cloudera was in the right market at the right time.

And for a while things went well. Cloudera rode the Hadoop startup wave, garnering a cool billion in funding along the way, including a stunning $740 million check from Intel Capital in 2014. It then went public in 2018 to much fanfare.

But the markets had already started to shift by the time of its public debut. Hadoop, a highly labor-intensive way to manage data, was being supplanted by cheaper and less complex cloud-based solutions.

“The excitement around the original promise of the Hadoop market has contracted significantly. It’s incredibly expensive and complex to get it working effectively in an enterprise context,” Casey Aylward, an investor at Costanoa Ventures told TechCrunch.

The company likely saw that writing on the wall when it merged with another Hadoop-based company, Hortonworks in 2019. That transaction valued the combined entity at $5.2 billion, almost the same amount it sold for yesterday, two years down the road. The decision to sell and go private may also have been spurred by Carl Icahn buying an 18% stake in the company that same year.

Looking to the future, Cloudera’s sale could provide the enterprise unicorn room as it regroups.

Patrick Moorhead, founder and principal analyst at Moor Insight & Strategies sees the deal as a positive step for the company. “I think this is good news for Cloudera because it now has the capital and flexibility to dive head first into SaaS. The company invented the entire concept of a data life cycle, implemented initially on premises, then extended to private and public clouds,” Moorhead said.

How to ensure data quality in the era of Big Data

Adam Ronthal, Gartner Research VP agrees that it at least gives Cloudera more room to make necessary adjustments its market strategy as long as it doesn’t get stifled by its private equity overlords. “It should give Cloudera an opportunity to focus on their future direction with increased flexibility — provided they are able to invest in that future and that this does not just focus on cost cutting and maximizing profits. Maintaining a culture of innovation will be key,” Ronthal said.

Which brings us to the two purchases Cloudera also announced as part of its news package.

If you want to change direction in a hurry, there are worse ways than via acquisitions. And grabbing Datacoral and Cazena should help Cloudera alter its course more quickly than it could have managed on its own.

“[The] two acquisitions will help Cloudera capture some of the value on top of the lake storage layer — perhaps moving into different data management features and/or expanding into the compute layer for analytics and AI/ML use cases, where there has been a lot of growth and excitement in recent years,” Alyward said.

Chandana Gopal, Research Director for the future of intelligence at IDC agrees that the transactions give Cloudera some more modern options that could help speed up the data wrangling process. “Both the acquisitions are geared towards making the management of cloud infrastructure easier for end-users. Our research shows that data prep and integration takes 70%-80% of an analyst’s time versus the time spent in actual analysis. It seems like both these companies’ products will provide technology to improve the data integration/preparation experience,” she said.

The company couldn’t stay on the path it was on forever, certainly not with an activist investor breathing down its neck. Its recent efforts could give it the time away from public markets it needs to regroup. How successful Cloudera’s turnaround proves to be will depend on whether the private equity companies buying it can both agree on the direction and strategy for the company, while providing the necessary resources to push the company in a new direction. All of that and more will determine if these moves pay off in the end.

Cloudera to go private as KKR & CD&R grab it for $5.3B


By Ron Miller

Stemma launches with $4.8M seed to build managed data catalogue

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As companies increasingly rely on data to run their businesses, having accurate sources of data becomes paramount. Stemma, a new early stage startup, has come up with a solution, a managed data catalogue that acts as an organization’s source of truth.

Today the company announced a $4.8 million seed investment led by Sequoia with assorted individual tech luminaries also participating. The product is also available for the first time today.

Company co-founder and CEO Mark Grover says the product is actually built on top of the open source Amundsen data catalogue project that he helped launch at Lyft to manage its massive data requirements. The problem was that with so much data, employees had to kludge together systems to confirm the data validity. Ultimately manual processes like asking someone in Slack or even creating a Wiki failed under the weight of trying to keep up with the volume and velocity.

“I saw this problem first-hand at Lyft, which led me to create the open source Amundsen project with a team of talented engineers,” Grover said. That project has 750 users at Lyft using it every week. Since it was open sourced, 35 companies like Brex, Snap and Asana have been using it.

Toro snags $4M seed investment to monitor data quality

What Stemma offers is a managed version of Amundsen that adds additional functionality like using intelligence to show data that’s meaningful to the person who is searching in the catalogue. It also can add metadata automatically to data as it’s added to the catalogue, creating documentation about the data on the fly, among other features.

The company launched last fall when Grover and co-founder and CTO Dorian Johnson decided to join forces and create a commercial product on top of Amundsen. Grover points out that Lyft was supportive of the move.

Today the company has five employees, in addition to the founders and has plans to add several more this year. As he does that, he is cognizant of diversity and inclusion in the hiring process. “I think it’s super important that we continue to invest in diversity, and the two ways that I think are the most meaningful for us right now is to have early employees that are from diverse groups, and that is the case within the first five,” he said. Beyond that, he says that as the company grows he wants to improve the ratio, while also looking at diversity in investors, board members and executives.

The company, which launched during COVID is entirely remote right now and plans to remain that way for at least the short term. As the company grows, they will look at ways to build camaraderie like organizing a regular cadence of employee offsite events.

How to ensure data quality in the era of Big Data


By Ron Miller

Databricks introduces Delta Sharing, an open source tool for sharing data

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Databricks launched its fifth open source project today, a new tool called Delta Sharing designed to be a vendor neutral way to share data with any cloud infrastructure or SaaS product, so long as you have the appropriate connector. It’s part of the broader Databricks open source Delta Lake project.

As CEO Ali Ghodsi points out, data is exploding and moving data from Point A to Point B is an increasingly difficult problem to solve with proprietary tooling. “The number one barrier for organizations to succeed with data is sharing data, sharing it between different views, sharing it across organizations — that’s the number one issue we’ve seen in organizations,” Ghodsi explained.

Delta Sharing is an open source protocol designed to solve that problem. “This is the industry’s first ever open protocol, an open standard for sharing a data set securely. […] They can standardize on Databricks or something else. For instance, they might have standardized on using AWS Data Exchange, Power BI or Tableau — and they can then access that data securely.”

The tool is designed to work with multiple cloud infrastructure and SaaS services and out of the gate there are multiple partners involved including the Big Three cloud infrastructure vendors Amazon, Microsoft and Google, as well as data visualization and management vendors like Qlik, Starburst, Collibra and Alation and data providers like Nasdaq, S&P and Foursquare

Ghodsi said the key to making this work is the open nature of the project. By doing that and donating it to The Linux Foundation, he is trying to ensure that it can work across different environments. Another big aspect of this is the partnerships and the companies involved. When you can get big name companies involved in a project like this, it’s more likely to succeed because it works across this broad set of popular services. In fact, there are a number of connectors available today, but Databricks expects that number to increase over time as contributors build more connectors to other services.

Why one Databricks investor thinks the company may be undervalued

Databricks operates on a consumption pricing model much like Snowflake, meaning the more data you move through its software, the more money it’s going to make, but the Delta Sharing tool means you can share with anyone, not just another Databricks customer. Ghodsi says that the open source nature of Delta Sharing means his company can still win, while giving customers more flexibility to move data between services.

The infrastructure vendors also love this model because the cloud data lake tools move massive amounts of data through their services and they make money too, which probably explains why they are all on board with this.

One of the big fears of modern cloud customers is being tied to a single vendor as they often were in the 1990s and early 2000s when most companies bought a stack of services from a single vendor like Microsoft, IBM or Oracle. On one hand, you had the veritable single throat to choke, but you were beholden to the vendor because the cost of moving to another one was prohibitively high. Companies don’t want to be locked in like that again and open source tooling is one way to prevent that.

Databricks was founded in 2013 and has raised almost $2 billion since. The latest round was in February for $1 billion at a $28 billion valuation, an astonishing number for a private company. Snowflake, a primary competitor, went public last September. As of today, it has a market cap of over $66 billion.

Airbyte announces $26M Series A for open-source data connector platform


By Ron Miller

AWS releases tool to open source that turns on-prem software into SaaS

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AWS announced today that it’s releasing a tool called AWS SaaS Boost as open source distributed under the Apache 2.0 license. The tool, which was first announced at the AWS:re:Invent conference last year, is designed to help companies transform their on-prem software into cloud-based Software as a Service

In the charter for the software, the company describes its mission this way: “Our mission is to create a community-driven suite of extensible building blocks for Software-as-a-Service (SaaS) builders. Our goal is to foster an open environment for developing and sharing reusable code that accelerates the ability to deliver and operate multi-tenant SaaS solutions on AWS.”

What it effectively does is provide the tools to turn the application into one that lets you sign up users and let them use the app in a multi-tenant cloud context. Even though it’s open source, it is designed to get you to move your application into the AWS system where you can access a number of AWS services such as AWS CloudFormation, AWS Identity and Access Management (IAM), Amazon Route 53, Elastic Load Balancing, AWS Lambda (Amazon’s serverless tool), and Amazon Elastic Container Service (Amazon’s Kubernetes Service). Although presumably you could use alternative services if you were so inclined.

MongoDB switches up its open-source license

By making it open source, it gives companies who would need this kind of service access to the source code, giving them a comfort level and an ability to contribute to the project to expand upon the base product and give back to the community. That makes it a win for users who get flexibility and the benefit of a community behind the tool, and a win for AWS, which gets that community working on the tool to improve and enhance it over time.

“Our objective with AWS SaaS Boost is to get great quality software based on years of experience in the hands of as many developers and companies as possible. Because SaaS Boost is open source software, anyone can help improve it. Through a community of builders, our hope is to develop features faster, integrate with a wide range of SaaS software, and to provide a high quality solution for our customers regardless of company size or location,” Amazon’s Adrian De Lucan wrote in a blog post announcing the intent to open source SaaS Boost.

This announcement comes just a couple of weeks after the company open sourced its Deep Racer device software, which runs its machine-learning fueled mini race cars. That said, Amazon has had a complex relationship with the open source in the past couple of years, where companies like MongoDB, Elastic and CockroachDB have altered their open source licenses to prevent Amazon from making their own hosted versions of these software packages.

Why AWS is building tiny AI race cars to teach machine learning


By Ron Miller

Emerging open cloud security framework has backing of Microsoft, Google and IBM

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Each of the big cloud platforms has its own methodology for passing on security information to logging and security platforms, leaving it to the vendors to find proprietary ways to translate that into a format that works for their tool. The Cloud Security Notification Framework (CSNF), a new working group that includes Microsoft, Google and IBM is trying to create a new open and standard way of delivering this information.

Nick Lippis, who is co-founder and co-chairman of ONUG, an open enterprise cloud community, which is the primary driver of CSNF says that what they’ve created is part standard and part open source. “What we’ve been really focusing on is how do we automate governance on the cloud. And so security was the place that was ripe for that where we can actually provide some value right away for the community,” he said.

While they’ve pulled in some of the big cloud vendors, they’ve also got large companies who consume cloud services like FedEx, Pfizer and Goldman Sachs. Conspicuously missing from the group is AWS, the biggest player in the cloud infrastructure market by far. But Lippis says that he hopes as the project matures, other companies including AWS will join.

“There’s lots of security programs and industry programs that get out there and that people are asking them to join, and so some companies want to wait to see how well this pans out [before making a commitment to it],” Lippis said. His hope is that over time, that Amazon will come around and join the group, but in the meantime they are working to get to the point everyone in the community will feel good about what they’re doing.

The idea is to start with security alerts and find a way to build a common format to give companies the same kind of system they have in the data center to track security alerts in the cloud. The way they hope to do that is with this open dialogue between the cloud vendors and the companies involved with the group.

“So the structure of that is that there’s a steering committee that is chaired by CISOs from these large cloud consumer brands, and also the cloud providers, and they provide voting and direction. And then there’s the working group where all the work is done. The beauty of what we do is that we have now consumers and also providers working together and collaborating,” he said.

FIDO Alliance and W3C have a plan to kill the password

Don Duet, a member of ONUG, who is CEO and co-founder of Concourse Labs, has been involved in the formation of the CSNF. He says to keep the project focused they are looking at this as a data management problem and they are establishing a common vocabulary for everyone to work within the group.

“How do you build a consensus on what are the types of terms that everybody can agree on and then you build the underlying basis so that the experts in your resource providers in this case, Cloud Service Providers, can bless how their data [connects] to those common standards,” Duet explained.

He says that particular problem is more of an organizational problem than a technical one, getting the various stakeholders together and just building consensus around this. At this point, they have that process in place and the next step is proving it by having the various companies involved in this test it out in the coming months.

After they get past the testing phase, in October they plan to actually demonstrate what this looks like in a before and after scenario, with the new framework and without it. As the group works toward these goals, the hope is that eventually the framework will become more established and other companies and vendors will come on board and make this a more standard way of sharing security alerts. If all goes well, they hope to build in other security information into this framework over time.

Solving the security challenges of public cloud


By Ron Miller

Tecton teams with founder of Feast open source machine learning feature store

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Tecton, the company that pioneered the notion of the machine learning feature store, has teamed up with the founder of the open source feature store project called Feast. Today the company announced the release of version 0.10 of the open source tool.

The feature store is a concept that the Tecton founders came up with when they were engineers at Uber. Shortly thereafter an engineer named Willem Pienaar read the founder’s Uber blog posts on building a feature store and went to work building Feast as an open source version of the concept.

“The idea of Tecton [involved bringing] feature stores to the industry, so we build basically the best in class, enterprise feature store. […] Feast is something that Willem created, which I think was inspired by some of the early designs that we published at Uber. And he built Feast and it evolved as kind of like the standard for open source feature stores, and it’s now part of the Linux Foundation,” Tecton co-founder and CEO Mike Del Balso explained.

Tecton later hired Pienaar, who is today an engineer at the company where he leads their open source team. While the company did not originally start off with a plan to build an open source product, the two products are closely aligned, and it made sense to bring Pienaar on board.

“The products are very similar in a lot of ways. So I think there’s a similarity there that makes this somewhat symbiotic, and there is no explicit convergence necessary. The Tecton product is a superset of what Feast has. So it’s an enterprise version with a lot more advanced functionality, but at Feast we have a battle-tested feature store that’s open source,” Pienaar said.

As we wrote in a December 2020 story on the company’s $35 million Series B, it describes a feature store as “an end-to-end machine learning management system that includes the pipelines to transform the data into what are called feature values, then it stores and manages all of that feature data and finally it serves a consistent set of data.”

Del Balso says that from a business perspective, contributing to the open source feature store exposes his company to a different group of users, and the commercial and open source products can feed off one another as they build the two products.

“What we really like, and what we feel is very powerful here, is that we’re deeply in the Feast community and get to learn from all of the interesting use cases […] to improve the Tecton product. And similarly, we can use the feedback that we’re hearing from our enterprise customers to improve the open source project. That’s the kind of cross learning, and ideally that feedback loop involved there,” he said.

The plan is for Tecton to continue being a primary contributor with a team inside Tecton dedicated to working on Feast. Today, the company is releasing version 0.10 of the project.

Tecton.ai nabs $35M Series B as it releases machine learning feature store


By Ron Miller

Camunda snares $98M Series B as process automation continues to flourish

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It’s clear that automated workflow tooling has become increasingly important for companies. Perhaps that explains why Camunda, a Berlin startup that makes open source process automation software, announced an €82 million Series B today. That translates into approximately $98 million U.S.

Insight Partners led the round with help from A round investor Highland Europe. When combined with the $28 million A investment from December 2018, it brings the total raised to approximately $126 million.

What’s attracting this level of investment says Jakob Freund, co-founder and CEO at Camunda is the company is solving a problem that goes beyond pure automation. “There’s a bigger thing going on which you could call end-to-end automation or end-to-end orchestration of endpoints, which can be RPA bots, for example, but also micro services and manual work [by humans],” he said.

He added, “Camunda has become this endpoint agnostic orchestration layer that sits on top of everything else.” That means that it provides the ability to orchestrate how the automation pieces work in conjunction with one another to create this full workflow across a company.

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The company has 270 employees and approximately 400 customers at this point including Goldman Sachs, Lufthansa, Universal Music Group, and Orange. Matt Gatto, managing director at Insight Partners sees a tremendous market opportunity for the company and that’s why his firm came in with such a big investment.

“Camunda’s success demonstrates how an open, standards-based, developer-friendly platform for end-to-end process automation can increase business agility and improve customer experiences, helping organizations truly transform to a digital enterprise,” Gatto said in a statement.

Camunda is not your typical startup. Its history actually dates back to 2008 as a business process management (BPM) consulting firm. It began the Camunda open source project in 2013, and that was the start of pivoting to become an open source software company with a commercial component built on top of that.

It took the funding at the end of 2018 because the market was beginning to catch up with the idea, and they wanted to build on that. It’s going so well that company reports it’s cash-flow positive, and will use the additional funding to continue accelerating the business.

Camunda hauls in $28M investment as workflow automation remains hot


By Ron Miller

Seven months after Drone acquisition, Harness announces significant updates

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The running line from any acquired company CEO is that the company can do so much more with resources of the company that acquired it than it could on its own. Just seven months after being acquired, Drone, co-founder Brad Rydzewski says that his company really has benefited greatly from being part of Harness, and today the company announced a significant overhaul of the open source project.

The artist formerly known as Drone is now called ‘Harness CI Community Edition’ and Rydzewski says the Harness CEO and founder Jyoti Bansal kept his word when he said he was 100% committed to continue developing the open source Drone product.

“Over the past seven months since the acquisition, a lot of community work has been around taking advantage of the resources that Harness has been able to afford us as a project — like having access to a designer, having access to professional writers — these are luxuries for most open source projects,” Rydzewski told me.

He says that having access to these additional resources has enabled him to bring a higher level of polish to the project that just wouldn’t have been possible without joining Harness. At the same time, he says the CI team, which has grown from the project’s two co-founders to 15 people, has also been able to build out the professional CI tool as it has become part of the Harness toolset.

Where top VCs are investing in open source and dev tools (Part 1 of 2)

Chief among the updates to the community edition is a new sleeker interface that has a much more professional look and feel, according to Rydzewski. In addition, developers can see how projects move along the pipeline in a visualization tool, while benefiting from real-time debugging tools and new governance and security features.

All of this is an embarrassment of riches for Rydzewski, who was used to working on a shoestring budget prior to joining Harness. “Drone came from very humble beginnings as an open source project, but now I think it can hold its own next to any product in the market today, even products that have raised hundreds of millions of dollars,” he said.

Harness makes first acquisition, snagging open-source CI company Drone.io


By Ron Miller

Docker nabs $23M Series B as as new developer focus takes shape

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It was easy to wonder what would become of Docker after it sold its enterprise business in 2019, but it regrouped last year as a cloud native container company focused on developers, and the new approach appears to be bearing fruit. Today, the company announced a $23 million Series B investment.

Tribe Capital led the round with participation from existing investors Benchmark and Insight Partners. Docker has now raised a total of $58 million including the $35 million investment it landed the same day it announced the deal with Mirantis .

To be sure, the company had a tempestuous 2019 when they changed CEOs twice, sold the enterprise division and looked to reestablish itself with a new strategy. While the pandemic made 2020 a trying time for everyone, Docker CEO Scott Johnston says that in spite of that, the strategy has begun to take shape.

“The results we think speak volumes. Not only was the strategy strong, but the execution of that strategy was strong as well,” Johnston told me. He indicated that the company added 1.7 million new developer registrations for the free version of the product for a total of more 7.3 million registered users on the community edition.

Docker regroups as cloud-native developer tool company

As with any open source project, the goal is to popularize the community project and turn a small percentage of those users into paying customers, but Docker’s problem prior to 2019 had been finding ways to do that. While he didn’t share specific numbers, Johnston indicated that annual recurring revenue (ARR) grew 170% last year, suggesting that they are beginning to convert more successfully.

Johnston says that’s because they have found a way to turn a certain class of developer in spite of a free version being available. “Yes, there’s a lot of upstream open source technologies, and there are users that want to hammer together their own solutions. But we are also seeing these eight-to-ten person ‘two pizza teams’ who want to focus on building applications, and so they’re willing to pay for a service,” he said.

That open source model tends to get the attention of investors because it comes with that built-in action at the top of the sales funnel. Tribe’s Arjun Sethi, whose firm led the investment, says his company actually was a Docker customer before investing in the company and sees a lot more growth potential.

“Tribe focuses on identifying N-of-1 companies — top-decile private tech firms that are exhibiting inflection points in their growth, with the potential to scale towards outsized outcomes with long-term venture capital. Docker fits squarely into this investment thesis[…],” Sethi said in a statement.

Johnston says as they look ahead to post-pandemic, he’s learned a lot since his team move out of the office last year. After surveying employees, they were surprised to learn that most have been happier working at home, having more time to spend with family, while taking away a grueling commute. As a result, he sees going virtual first, even after it’s safe to reopen offices.

That said, he is planning to offer a way to get teams together for in-person gatherings and a full company get-together once a year.

“We’ll be virtual first, but then with the savings of the real estate that we’re no longer paying for, we’re going to bring people together and make sure we have that social glue,” he said.

After selling enterprise biz, Docker lands $35M investment and new CEO


By Ron Miller

Yugabyte announces $48M Series C as cloud native database makes enterprise push

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As demand for cloud native applications is growing, Yugabyte, makers of the cloud native, open source YugabyteDB database are seeing a corresponding rise in demand for their products, especially with large enterprise customers. Today, the company announced a $48 million Series C financing round to help build on that momentum.

Lightspeed Venture Partners led the round with participation from Greenspring Associates, Dell Technologies Capital, Wipro Ventures and 8VC. Today’s round comes on the heels of the startup’s $30 million Series B last June, and brings the total raised to $103 million, according to the company.

Kannan Muthukkaruppan, Yugabyte co-founder and president, says the startup saw a marked increase in interest in both the open source and commercial offerings in 2020 as the pandemic pushed many companies to the cloud faster than they might have gone otherwise, something many startup founders have pointed out to me.

“The distributed SQL space is definitely heating up, and if anything over the last six months almost in every vector in terms of enterprise customers — from Fortune 500 companies across financial, retail, ISP or telcos — are putting Yugabyte in production to be the system of record database to meet some of their business critical services needs,” Muthukkaruppan told me.

In addition, he’s seeing a similar rise in the level of interest from the open source version of the product.”Similarly, the groundswell on the community and the open source adoption has been phenomenal. Our Slack [open source] user community quadrupled in 2020,” he said.

That kind of momentum led to the increased investor interest, says co-founder and CTO Karthik Ranganathan. “Some of the primary reasons to go and even ask for funding was that we realized we could accelerate some of this stuff, and we couldn’t do that with the original $30 million we had raised,” he said. The original thinking was to do a secondary raise in the $15-20 million, but multiple investors expressed interest in participating, and it ended up being a $48 million round when all was said and done.

Former Pivotal president Bill Cook came on board as CEO at the same time they were announcing their last funding round in June and brought some enterprise chops to the table. It was his job to figure out how to expand the market opportunity with larger high-value enterprise clients. “And so the last six or seven months has been about that, dealing with enterprise clients on one hand and then this emerging developer led cloud offering as well,” Cook said.

Grafana Labs launches observability stack for enterprise customers

The company has a three tier offering that includes the open source YugabyteDB. Then there is a fully managed cloud version called Yugabyte Cloud, and finally there is a self-managed cloud version of the database called Yugabyte Platform. The latter is especially attractive to large enterprise customers, who want to be in the cloud, but still want to maintain control of their data and infrastructure, and so choose to manage the cloud installation themselves.

The company started last year with 50 employees, doubled that to this point, and now expects to reach 200 by the end of this year. As they add employees, the leadership team is cognizant of the importance of building a diverse and inclusive workforce, while recognizing the challenges in doing so.

“It’s work in progress as always. We’ve added diversity candidates right along the whole spectrum as we’ve grown but from my perspective it’s never sufficient, and we just need to keep pushing on it hard, and I think as a leadership team we recognize that,” Cook said.

The three leaders of the company have been working together remotely now since the announcement in June, and had only met briefly in person prior to the pandemic shutting down offices, but they say that it has gone smoothly. And while they would obviously like to meet in person again when the time is right, the momentum the company is experiencing shows that things are moving in the right direction, regardless of where they are getting their work done.

Yugabyte lands $30M Series B as open source database continues to flourish


By Ron Miller

Grafana Labs launches observability stack for enterprise customers

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Grafana Labs has created an open source observability trifecta that includes Prometheus for monitoring, Loki for logging and Tempo for tracing. Today, the company announced it was releasing enterprise versions of these open source projects in a unified stack designed specifically for the needs of large companies.

Company CEO Raj Dutt says that this product is really aimed at the largest companies in the world, who crave  control over their software. “We’re really going after at scale users who want a cutting edge observability platform based on these leading open source projects. And we are adding a lot of feature differentiation in the enterprise version along with 24/7 support from the experts, from the people who have actually created software,” he said.

Among those features is a set of plug-ins that lets these large customers pull data into the platform from leading enterprise software companies including Splunk, New Relic, MongoDB and Snowflake. The Enterprise Stack also provides enhanced authentication and security.

Dutt calls this product self-managed to contrast it with the managed cloud versions of the product the company already has been offering for some time. “We have two main products, Grafana Cloud and now Grafana Enterprise Stack. Grafana Cloud is our hosted deployment model, and the Grafana Enterprise Stack is essentially licensed software that customers are free to run however they want, whether that’s on prem, in a colocation company like Equinix or on the cloud vendor of their choice,” Dutt explained.

Grafana Labs adds a free tier to its managed observability platform

They can also mix and match their deployments across the cloud or on-prem in a hybrid style, and the large enterprise customers that the company is going after with this product should like that flexibility. “It also allows them to hybridize their deployments, so they may decide to use the cloud for metrics, but their logs contain a lot of sensitive information [and they want to deploy that on prem]. And since it’s a composable stack, they may have a hybrid deployment that’s partly in the cloud cloud and partly on prem,” he said.

When you combine this new enterprise version with the managed cloud version that already exists, it gives Grafana another potentially large revenue source. The open source products act as a driver, giving Grafana a way into these companies, and Dutt says they know of over 700,000 instances of the open source products in use across the world.

While the open source business model usually only turns a fraction of these users into paying customers, having numbers like this gives the company a huge head start and it’s gotten the attention of investors. The company has already raised over $75 million including a $24 million Series A 2019 and a $50 million Series B in 2020.

Grafana Labs nabs $24M Series A for open source-based data analytics stack


By Ron Miller

Databricks raises $1B at $28B valuation as it reaches $425M ARR

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Another hour, another billion-dollar round. That’s how February is kicking off. This time it’s Databricks, which just raised $1 billion Series G at a whopping $28 billion post-money valuation.

Databricks is a data-and-AI focused company that interacts with corporate information stored in the public cloud.

News of the new round began leaking last week. Franklin Templeton led the round, which also included new investors Fidelity and Whale Rock. Databricks also raised part of the capital from major cloud vendors including AWS, Alphabet via its CapitalG vehicle, and Salesforce Ventures. Microsoft is a previous investor, and it took part in the round as well.

But we’re not done! Other prior investors including a16z, T. Rowe Price, Tiger Global, BlackRock, and Coatue were also involved along with Alkeon Capital Management.

Consider that Databricks just raised a bushel of capital from a mix of cloud companies it works with, public investors it wants as shareholders when it goes public, and some private money that is enjoying a stiff markup from their last check into the company.

The company has made its mark with a series of four open source products with a core data lake product call Delta Lake leading the way. You may recall that another hot data lake company, Snowflake, raised almost a half a billion dollars on a $12.4 billion valuation a year ago before going public last September with a valuation twice that. Databricks has already exceeded that public valuation with this round — as a private company.

When we spoke to Databricks CEO Ali Ghodsi at the time of his company’s $400 million round in 2019, one which valued the company at $6.2 billion at the time, he said his company was the fastest growing enterprise cloud software companies ever, and that’s saying something.

The company makes money by offering each of those open source products as a software service and it’s doing exceedingly well at it, so much so that investors were tripping over each other to be part of this deal. In fact, Ghodsi said in a conversation with TechCrunch today that his company had targeted a much more modest $200 million raise, but that figure grew as more parties wanted to invest funds into the company. Even with that, Databricks had to turn capital away, he added, after deciding to cap the round at $1 billion.

The extra $800 million that the company raised will be used for M&A opportunities with an eye on talent, spend on establishing a Lakehouse concept, international expansion, while also expanding its engineering team, the CEO said.

Databricks crossed $350M run rate in Q3, up from $200M one year ago

Ghodsi also made clear that he does not intend to let the percentage of revenue that the company spends on R&D to drop, as is common at modern software companies — as many SaaS companies grow, they expend more of their revenue on sales and marketing efforts over product spend, something that Databricks wants to avoid by continuing to invest in engineering talent.

Why? Because Ghodsi says that the pace of innovation in AI is so rapid that IP becomes outdated in just a few years. That means that companies that want to lead in this space will have to stay on the bleeding edge of their market or fall back swiftly.

The Databricks model appears to be working well, with the company closing 2020 at $425 million in annual recurring revenue, or ARR. That figure, up 75% from the year-ago period, is also up from a $350 million run rate at the end of its Q3 2020. (For more on Databricks’ business, product and growth, head here.)

Notably Ghodsi told TechCrunch that this deal only started to come together in December. It’s February 1st today, which means that it took on this bushel of new funding remarkably quickly.

Finally, at $425 million in ARR, is the CEO worried about having a valuation sitting at roughly a 65x multiple? Ghodsi said that he is not. He said that he told his company during an all-hands earlier today that the AI market is a long journey, one that he hopes to be on for decades, and the stock market will go up and down. His point, as far as I could read into it, was that so long as Databricks keeps growing as it has, its valuation will take care of itself (and that seems to be the case so far with this company).

What’s certainly true is that Databricks is now as rich as it has ever been, as large as it has ever been, and in a market that is maturing. Let’s see what it can do with all this money.

Databricks announces $400M round on $6.2B valuation as analytics platform continues to grow


By Alex Wilhelm