What happened
The Robot Report Podcast Episode 254 featured Doug Pagnutti, industrial developer advocate at Tiger Data, discussing how time series databases like TimescaleDB improve industrial automation, robotics, and AI applications by integrating with sensors, managing data at scale, and optimizing performance on cloud and edge systems.
Why it matters
Time series databases address a critical infrastructure challenge for robotics and industrial IoT (IIoT) deployments. Pagnutti has 12+ years in oil and gas and manufacturing automation with experience in PLCs, robots, and SCADA systems, and now helps automation engineers tackle time-series data infrastructure—a key bottleneck as robotics systems collect and process growing volumes of sensor data in real time.
What to watch
Tiger Data's TimescaleDB extends PostgreSQL with time-series primitives, columnar storage, and automatic partitioning to keep queries fast on live data without requiring data pipelines, migration, or a second database system.
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The episode addresses a growing infrastructure challenge in industrial robotics and IIoT. As robots and automated systems collect real-time sensor data from PLCs, SCADA systems, and edge devices, the volume and velocity of time-series data can overwhelm traditional database architectures—a problem Pagnutti has encountered across oil, gas, and manufacturing sectors. Time series databases like TimescaleDB solve this by extending PostgreSQL with specialized primitives (columnar storage, automatic partitioning) designed for the access patterns of time-stamped data, eliminating the need for teams to maintain multiple database systems or expensive data pipelines. Pagnutti's 12+ years bridging the operational technology (OT) and information technology (IT) gap positions him to advise automation engineers on scaling IIoT deployments—a critical need as industrial organizations digitize their edge infrastructure.
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