I’ve never seen the type of customer traction that Timescale is seeing right now.

I’m excited to announce that I’m joining Ajay, Mike and the rest of the team at Timescale to help scale revenue and partnerships!

Since leaving Twitter a little over a year ago, I’ve spent time working on a few startup ideas of my own and helping a select group of startups here in NYC with their go-to-market strategy.

Over the course of the last year I’ve spoken with Ajay about Timescale and what he’s building here. Earlier this year, we started to think about ways to work together, and as I learned more I did everything I could to convince Ajay to let me come onboard.

The Incoming Wave of High-Resolution Data

The rise of connected machines leading to a rise of high-resolution data.

Big data is a term that’s been (over)used for the last 10+ years so it now seems old hat. I believe that’s shortsighted as we’re just starting to enter an era where internet connected devices become truly pervasive. As machines and devices from consumer wearables to sensors on $100 million excavators become commoditized, the deluge of data is already growing exponentially.

Not only are all machines becoming networked, organizations are starting to realize that there’s substantial strategic benefit to capturing greater data resolution. Instead of being content to track data on an hourly or minute-by-minute basis, organizations are now interested in the type of analysis they can do if they’re able to collect and analyze data on a second or sub-second basis.

It’s not cheap to fix this thing.

This increase in the desire for data resolution means that companies which have historically taken their data and stored it in data warehouses (to sit, un-analyzed) are now craving an operational analytics solution that can take the data they’re collecting and make sense of it. As companies are starting to explore how to do these types of analyses, they’re realizing that this type of data has a common characteristic: it’s time-series data.

Enter TimescaleDB

What is time-series data? It’s typically data that is collected (usually) in order with time as the primary variable. This kind of data is found in manufacturing and other industries with large-scale machines where sensors are used to make sure everything is operating as it should. It’s also found in financial services companies to analyze the ebb and flow of the global markets. In fact, time-series data is increasingly found in companies of all kinds to monitor the operations of critical infrastructure.

TimescaleDB is the first open source time-series database built for scalability and advanced analytics. Packaged as a PostgreSQL extension, TimescaleDB solves one of the biggest issues for any relational database: the ability to scale for time-series workloads.

The big challenge for many companies is combining the efficient collection and storage of an ever increasing amount of time series data with the ability to do advanced analytics on that data. Because it’s packaged as a PostgreSQL extension, TimescaleDB enables businesses to use full SQL and combine their time-series data with other business data they may be collecting in relational databases including data from their CRM or ERP. No other open source time series database today offers this capability.

Why did I join now?

I’ve never seen the type of customer traction that Timescale is seeing right now. We have an incredibly passionate community of developers and businesses who are building fascinating applications using TimescaleDB.

I’ve never seen the type of customer traction that Timescale is seeing right now.

Ajay shared some growth metrics in his post discussing the $16 million that Timescale raised from Benchmark, NEA and Two Sigma Ventures. In just over a year, TimescaleDB has seen hundreds of thousands of downloads and tremendous interaction on Github and our active ~1,500 member Community Slack group.

Some companies using TimescaleDB in novel ways include:

  • The European Space Agency using TimescaleDB to collect solar orbital data.
  • STE Energy, which is backing operational dashboards across 47 globally distributed power plants.
  • LAIKA, a major animation studio, which uses Timescale to automate their PostgreSQL partition management and store all machine event data.
  • A major financial services company using TimescaleDB for geo-temporal asset tracking, replacing legacy database architecture.

Why me?

I’ve been helping technology companies scale revenue for most of my career. Most recently, I was a Director of Sales at Twitter, by way of their acquisition of TapCommerce where I was the first business hire. While at TapCommerce I built and led a 15-person sales team, growing revenue from $0-$18 million in about two years. Ultimately we were acquired by Twitter for $100 million.

During my time at TapCommerce, I saw our engineering team struggle to wrangle and operationalize the data we were collecting as a demand-side platform doing hundreds of thousands of queries per second. Speaking with the team about the ways they were solving that problem helped me understand how important data infrastructure is to making businesses successful.

The opportunity to tackle customer acquisition and monetization at an open source company with hundreds of thousands of downloads and an active community got the sales ops nerd in me very excited. Working closely with customers who are trying to solve tough operational problems using an innovative database is especially gratifying. I also enjoy putting data-driven processes in place to help companies and teams grow as operational complexity begins to compound.

While at Twitter, I helped lead a 25-person sales team that worked directly with some of Twitter’s largest customers. We helped those customers engage with the community on Twitter in innovative ways to drive revenue for their business. As I spoke more with Ajay and Mike, I saw some clear parallels between my experience at Twitter and the challenge of harnessing a passionate open source community at Timescale.

As I learned more about the opportunity Timescale has to help businesses capture and analyze their time-series data, I knew I could use my background helping startups scale revenue and customer adoption to help.

The cherry on top

Over the course of the last few months as I’ve gotten to know the entire Timescale team, I can tell that there’s something really special happening here. Mike and Ajay have brought together a truly great group full of passionate engineers, designers, marketers, community evangelists and more.

Everyone at Timescale is working together toward a common goal: to help businesses capture greater insights from the exponentially increasing amount of data they’re collecting. It’s an exciting opportunity and I couldn’t be more excited to join such a fantastic team at this moment. I look forward to seeing what we can all build together!

We’re hiring (especially on the business side) so if you’d like to be part of what we’re doing a Timescale, please reach out to me directly tim AT timescale DOT com.

And if you’d like to learn more about TimescaleDB, please check out our GitHub (stars always appreciated), and please let us know how we can help.