Unlocking the Power of Time Series Databases for Industrial and Robotic Systems

About this episode

In this episode, Doug Pagnutti, Developer Advocate at Tiger Data, discusses how time series databases like TimescaleDB are transforming industrial automation, robotics, and AI applications. He shares insights on integrating these databases with various sensors, managing data at scale, and optimizing performance both on the cloud and on the edge. Key Topics: - The role of time series data in robotics and industrial automation - How TimescaleDB extends PostgreSQL for high-performance time series workloads - Differences between open source and managed cloud versions - Strategies for integrating various industrial controllers and messaging pipelines - Techniques for managing intermittent connectivity with edge devices - Advanced tools like continuous aggregates and data compression for big data - Enabling multimodal data queries with hybrid search stacks - Future applications of time series data in AI-driven environments and energy systems - Best practices for storing telemetry, spatial, and metadata efficiently – SPONSORS – This episode is brought to you by Tiger Data Every growing Postgres database eventually hits a wall. Queries slow down, dashboards lag, and teams consider adding a second database. Tiger Data, creators of TimescaleDB, extends Postgres with time-series primitives, columnar storage, and automatic partitioning so your queries stay fast on live data. No pipelines, no migration, no second system. Just Postgres, built for the workload you actually have. Try it free at https://www.tigerdata.com/go/trial?utm_source=content-syndication&utm_medium=referral&utm_campaign=robotics-ads