DOP 337: Nanoseconds Matter - InfluxDB and the Future of Real-Time Data

Episode 337

Show Notes

#337: Time series databases have become essential infrastructure for the physical AI revolution. As automation extends into manufacturing, autonomous vehicles, and robotics, the demand for high-resolution, low-latency data has shifted from milliseconds to nanoseconds. The difference between a general-purpose database and a specialized time series solution is the difference between a minivan and an F1 car - both will get around the track, but only one is built for the demands of real-time operational workloads.

The open source business model continues to evolve in unexpected ways. While companies like Elastic and Redis have seen hyperscalers fork their projects, a new partnership paradigm is emerging. Amazon Web Services now pays to license InfluxDB and offers it as a managed service, signaling a shift toward collaboration rather than competition. This approach benefits everyone: vendors maintain development velocity, cloud providers get workloads on their platforms, and customers receive better-supported products.

Evan Kaplan, CEO of InfluxData, joins Darin and Viktor to discuss the trajectory from observability metrics to physical world instrumentation, why deterministic models matter more than probabilistic ones when your robot might run over your cat, and what it takes to build a sustainable open source company over a decade-plus journey.

Frequently Asked Questions

Why use a time series database instead of PostgreSQL or MySQL?

Evan Kaplan of InfluxData explains on DevOps Paradox episode 337 that general purpose databases do not optimize for the thing a time series workload already knows: its index is primarily time. Specializing lets you change ingest rate, write time, query speed and storage cost together, and skipping that means paying all of those prices. He compares using a relational database for the job to entering a minivan in a Formula 1 race.

How long should you keep time series data?

Evan Kaplan tells Darin Pope on DevOps Paradox episode 337 that the retention period is whatever separates signal from noise for the problem being solved. The common pattern is collecting high resolution data for a short window, then downsampling and storing the result for a long one. Viktor Farcic adds that going finer than you need costs money and performance. Kaplan counters that you do not always know the needed period in advance.

Who does not need a time series database?

Evan Kaplan says on DevOps Paradox episode 337 that light instrumentation feeding a dashboard does not need one, and a general purpose database or an observability vendor will do. The people who do need one run operational workloads where something depends on the data rather than just a chart. His example is a customer collecting from ten million devices that has to act on readings in under fifteen milliseconds.

Why does physical AI need deterministic models rather than probabilistic ones?

Evan Kaplan argues on DevOps Paradox episode 337 that probabilistic models work fine for language and digital data, but systems acting on the physical world need deterministic ones. His illustration is blunt: he does not want his robot running over his cat, or a self-driving car hitting a pedestrian. He also notes that the physical world offers effectively infinite data to collect, unlike the digital corpus that has largely been scraped already.

Why has InfluxDB kept a permissive open source license?

Evan Kaplan tells Viktor Farcic on DevOps Paradox episode 337 that InfluxData stayed on MIT and Apache while most competitors moved to restrictive secondary licenses, and that he would make the same choice starting over today. He describes the approach as open core, meaning not everything goes into the open source project. The company also has committers on Apache Arrow and Apache DataFusion rather than contributing only to its own code.

Why did AWS partner with InfluxData rather than fork it?

Evan Kaplan says on DevOps Paradox episode 337 that Amazon both licenses and pays for InfluxDB and sells it as Timestream for InfluxDB. He reads the shift as Amazon having learned what maintaining its own forks of Elasticsearch and Redis actually costs, measured against the goal that matters more to it: getting workloads onto the platform. Data has gravity, so once it lands there the other services follow.

What is the DevOps Paradox podcast?

DevOps Paradox is a weekly podcast co-hosted by Darin Pope and Viktor Farcic, covering DevOps, platform engineering, and modern software delivery. Episode 337 brings in Evan Kaplan of InfluxData to work through when a time series database earns its place, how long to keep the data, and why physical automation changes the requirements. Every episode page carries the audio, the video, and a full transcript.

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Guests

Evan Kaplan

Evan Kaplan

Evan Kaplan is a seasoned entrepreneur and technology leader with over 25 years of executive experience. He is currently the CEO of InfluxData, the company behind InfluxDB, the leading time series database. Since joining InfluxData in 2016, he has played a key role in scaling the company to meet the growing demand for time series data solutions, especially for IoT, Industrial IoT, and AI applications. Previously, Evan served as President and CEO of iPass Corporation, where he led its transformation into a global leader in Wi-Fi connectivity. Earlier in his career, he founded Aventail Corporation, a pioneering SSL VPN company later acquired by Dell, and served as an Executive in Residence at Trinity Ventures.

Beyond technology, Evan is active in philanthropy and venture investing. He is a longtime board member and Treasurer of One Heart Worldwide, a nonprofit that partners with the Nepalese government to improve maternal and neonatal healthcare in remote communities. He also serves on the board of and advises several early-stage AI companies, including Diffblue and Botpress.

An experienced alpinist, Evan is a veteran of multiple Himalayan expeditions, reflecting his passion for adventure and endurance. He holds a Bachelor of Science in Environmental Science from Western Washington University and an MBA from the University of Washington.

Hosts

Darin Pope

Darin Pope

Viktor Farcic

Viktor Farcic

Viktor Farcic is a member of the Google Developer Experts and Docker Captains groups, and published author.

His big passions are DevOps, Containers, Kubernetes, Microservices, Continuous Integration, Delivery and Deployment (CI/CD) and Test-Driven Development (TDD).

He often speaks at community gatherings and conferences.

He has published DevOps Paradox and Test-Driven Java Development.

His random thoughts and tutorials can be found in his blog The DevOps Toolkit.