Why Industrial IoT Data Breaks Traditional Databases — and What to Do About It
Industrial IoT data is getting harder to manage. More sensors. More data types. More operational decisions that cannot wait for a batch window. And most databases — built for a different era — are not keeping up.
In this session, Dr. Johannes Held, Principal at Dataciders, joins Gregor Bauer, VP of Customer Engineering at CrateDB, for a direct conversation about what breaks in production, why high-cardinality time-series data is the hardest problem to solve, and how Dataciders is solving it for industrial clients today.
Topics include:
- Why classic architectures fail at data volume and variety — and what the failure looks like in practice
- How CrateDB handles high-cardinality time-series data without pre-aggregation or proprietary query languages
- What drop-in PostgreSQL compatibility means for real-world adoption speed
- How to keep a database that scales as requirements change — without a migration project every three years
- Data sovereignty and European deployment considerations for regulated industrial environments
About CrateDB
CrateDB is a distributed SQL database for real-time analytics, search, and AI. It combines structured, semi-structured, and unstructured data in one scalable system, enabling organizations to analyze massive data volumes instantly. Businesses use CrateDB to power live dashboards, event-driven applications, and AI insights, on any infrastructure, from cloud to edge.Our Speakers
Dr. Johannes Held is a Principal at Dataciders, where he leads interdisciplinary teams supporting industrial clients across data foundations, integration layers, reporting, and custom applications. He holds a PhD in data management from Friedrich Alexander Universität Erlangen Nürnberg and brings over a decade of experience building the data strategies that make reliable operational analytics possible.
Gregor leads the team responsible for helping customers unlock the full potential of real-time data and distributed SQL
technologies. His focus lies in enabling organizations to build modern, data-driven applications that scale effortlessly
from IoT and time-series analytics to edge and cloud deployments.
Stephane specializes in data-driven growth strategies, data integration, data analytics and AI innovation. He leads global marketing across brand, content, and product-led growth, connecting data engineers and architects with the distributed SQL database built for high-velocity, high-cardinality workloads.