Personal blog of Yzmir Ramirez

Timescale, makers of the open-source TimescaleDB time series database, announced a $40 million Series B financing round today. The investment comes just over two years after it got a $15 million Series A.

Redpoint Ventures led today’s round, with help from existing investors Benchmark, New Enterprise Associates, Icon Ventures and Two Sigma Ventures. The company reports it has now raised approximately $70 million.

TimescaleDB lets users measure data across a time dimension, so anything that would change over time. “What we found is we need a purpose-built database for it to handle scalability, reliability and performance, and we like to think of ourselves as the category-defining relational database for time series,” CEO and co-founder Ajay Kulkarni explained.

He says that the choice to build their database on top of Postgres when it launched four years ago was a key decision. “There are a few different databases that are designed for time series, but we’re the only one where developers get the purpose-built time series database plus a complete Postgres database all in one,” he said.

While the company has an open-source version, last year it decided rather than selling an enterprise version (as it had been), it was going to include all of that functionality in the free version of the product and place a bet entirely on the cloud for revenue.

“We decided that we’re going to make a bold bet on the cloud. We think cloud is where the future of database adoption is, and so in the last year […] we made all of our enterprise features free. If you want to test it yourself, you get the whole thing, but if you want a managed service, then we’re available to run it for you,” he said.

The community approach is working to attract users, with over 2 million monthly active databases, some of which the company is betting will convert to the cloud service over time. Timescale is based in New York City, but it’s a truly remote organization, with 60 employees spread across 20 countries and every continent except Antarctica.

He says that as a global company, it creates new dimensions of diversity and different ways of thinking about it. “I think one thing that is actually kind of an interesting challenge for us is what does D&I mean in a totally global org. A lot of people focus on diversity and inclusion within the U.S., but we think we’re doing better than most tech companies in terms of racial diversity, gender diversity,” he said.

And being remote-first isn’t going to change even when we get past the pandemic. “I think it may not work for every business, but I think being remote first has been a really good thing for us,” he said.

It’s a big day for Timescale, makers of the open-source time-series database, TimescaleDB. The company announced a $15 million investment and a new enterprise version of the product.

The investment is technically an extension of the $12.4 million Series A it raised last January, which it’s referring to as A1. Today’s round is led by Icon Ventures, with existing investors Benchmark, NEA and Two Sigma Ventures also participating. With today’s funding, the startup has raised $31 million.

Timescale makes a time-series database. That means it can ingest large amounts of data and measure how it changes over time. This comes in handy for a variety of use cases, from financial services to smart homes to self-driving cars — or any data-intensive activity you want to measure over time.

While there are a number of time-scale database offerings on the market, Timescale co-founder and CEO Ajay Kulkarni says that what makes his company’s approach unique is that it uses SQL, one of the most popular languages in the world. Timescale wanted to take advantage of that penetration and build its product on top of Postgres, the popular open-source SQL database. This gave it an offering that is based on SQL and is highly scalable.

Timescale admittedly came late to the market in 2017, but by offering a unique approach and making it open source, it has been able to gain traction quickly. “Despite entering into what is a very crowded database market, we’ve seen quite a bit of community growth because of this message of SQL and scale for time series,” Kulkarni told TechCrunch.

In just over 22 months, the company has more than a million downloads and a range of users from older guard companies like Charter, Comcast and Hexagon Mining to more modern companies like Nutanix and and TransferWise.

With a strong base community in place, the company believes that it’s now time to commercialize its offering, and in addition to an open-source license, it’s introducing a commercial license. “Up until today, our main business model has been through support and deployment assistance. With this new release, we also will have enterprise features that are available with a commercial license,” Kulkarni explained.

The commercial version will offer a more sophisticated automation layer for larger companies with greater scale requirements. It will also provide better lifecycle management, so companies can get rid of older data or move it to cheaper long-term storage to reduce costs. It’s also offering the ability to reorder data in an automated fashion when that’s required, and, finally, it’s making it easier to turn the time series data into a series of data points for analytics purposes. The company also hinted that a managed cloud version is on the road map for later this year.

The new money should help Timescale continue fueling the growth and development of the product, especially as it builds out the commercial offering. Timescale, which was founded in 2015 in NYC, currently has 30 employees. With the new influx of cash, it expects to double that over the next year.

Data is the lifeblood of the modern corporation, yet acquiring, storing, processing, and analyzing it remains a remarkably challenging and expensive project. Every time data infrastructure finally catches up with the streams of information pouring in, another source and more demanding decision-making makes the existing technology obsolete.

Few cities rely on data the same way as New York City, nor has any other city so shaped the technology that underpins our data infrastructure. Back in the 1960s, banks and accounting firms helped to drive much of the original computation industry with their massive finance applications. Today, that industry has been supplanted by finance and advertising, both of which need to make microsecond decisions based on petabyte datasets and complex statistical models.

Unsurprisingly, the city’s hunger for data has led to waves of database companies finding their home in the city.

As web applications became increasingly popular in the mid-aughts, SQL databases came under increasing strain to scale, while also proving to be inflexible in terms of their data schemas for the fast-moving startups they served. That problem spawned Manhattan-based MongoDB, whose flexible “NoSQL” schemas and horizontal scaling capabilities made it the default choice for a generation of startups. The company would go on to raise $311 million according to Crunchbase, and debuted late last year on NASDAQ, trading today with a market cap of $2 billion.

At the same time that the NoSQL movement was hitting its stride, academic researchers and entrepreneurs were exploring how to evolve SQL to scale like its NoSQL competitors, while retaining the kinds of features (joining tables, transactions) that make SQL so convenient for developers.

One leading company in this next generation of database tech is New York-based Cockroach Labs, which was founded in 2015 by a trio of former Square, Viewfinder, and Google engineers. The company has gone on to raise more than $50 million according to Crunchbase from a luminary list of investors including Peter Fenton at Benchmark, Mike Volpi at Index, and Satish Dharmaraj at Redpoint, along with GV and Sequoia.

While web applications have their own peculiar data needs, the rise of the internet of things (IoT) created a whole new set of data challenges. How can streams of data from potentially millions of devices be stored in an easily analyzable manner? How could companies build real-time systems to respond to that data?

Mike Freedman and Ajay Kulkarni saw that problem increasingly manifesting itself in 2015. The two had been roommates at MIT in the late 90s, and then went on separate paths into academia and industry respectively. Freedman went to Stanford for a PhD in computer science, and nearly joined the spinout of Nicira, which sold to VMware in 2012 for $1.26 billion. Kulkarni joked that “Mike made the financially wise decision of not joining them,” and Freedman eventually went to Princeton as an assistant professor, and was awarded tenure in 2013. Kulkarni founded and worked at a variety of startups including GroupMe, as well as receiving an MBA from MIT.

The two had startup dreams, and tried building an IoT platform. As they started building it though, they realized they would need a real-time database to process the data streams coming in from devices. “There are a lot of time series databases, [so] let’s grab one off the shelf, and then we evaluated a few,” Kulkarni explained. They realized what they needed was a hybrid of SQL and NoSQL, and nothing they could find offered the feature set they required to power their platform. That challenge became the problem to be solved, and Timescale was born.

In many ways, Timescale is how you build a database in 2018. Rather than starting de novo, the team decided to build on top of Postgres, a popular open-source SQL database. “By building on top of Postgres, we became the more reliable option,” Kulkarni said of their thinking. In addition, the company opted to make the database fully open source. “In this day and age, in order to get wide adoption, you have to be an open source database company,” he said.

Since the project’s first public git commit on October 18, 2016, the company’s database has received nearly 4,500 stars on Github, and it has raised $16.1 million from Benchmark and NEA .

Far more important though are their customers, who are definitely not the typical tech startup roster and include companies from oil and gas, mining, and telecommunications. “You don’t think of them as early adopters, but they have a need, and because we built it on top of Postgres, it integrates into an ecosystem that they know,” Freedman explained. Kulkarni continued, “And the problem they have is that they have all of this time series data, and it isn’t sitting in the corner, it is integrated with their core service.”

New York has been a strong home for the two founders. Freedman continues to be a professor at Princeton, where he has built a pipeline of potential grads for the company. More widely, Kulkarni said, “Some of the most experienced people in databases are in the financial industry, and that’s here.” That’s evident in one of their investors, hedge fund Two Sigma. “Two Sigma had been the only venture firm that we talked to that already had built out their own time series database,” Kulkarni noted.

The two also benefit from paying customers. “I think the Bay Area is great for open source adoption, but a lot of Bay Area companies, they develop their own database tech, or they use an open source project and never pay for it,” Kulkarni said. Being in New York has meant closer collaboration with customers, and ultimately more revenues.

Open source plus revenues. It’s the database way, and the next wave of innovation in the NYC enterprise infrastructure ecosystem.

 Businesses are gathering more and more information than they ever have before, whether it’s a manufacturer or a bank, and to Timescale CEO Ajay Kulkarni the existing database software soon won’t provide the horsepower they need. That’s why he and CTO Mike Freedman started Timescale, a new open source time series database software. The idea is that businesses increasingly… Read More