How to Use SQL for ML Feature Engineering on Time-Series Sensor Data
Discover how to leverage SQL for efficient feature engineering on time-series sensor data, enhancing machine learning model accuracy without memory bottlenecks.
Why Industrial Teams Are Moving from Flux and InfluxQL to Standard SQL
Explore the challenges of migrating between InfluxDB query languages and discover the advantages of standard SQL for industrial IoT analytics.
Comparing MongoDB, TimescaleDB, InfluxDB, and CrateDB for an IIoT Use-case
In this blog post, we compare how MongoDB, TimescaleDB, InfluxDB, and CrateDB perform for an industrial IoT use-case.
IoT Analytics at Scale: Architecture Guide for Industrial Data
Build real-time industrial IoT analytics with Telegraf, CrateDB, and Grafana. SQL examples, architecture patterns, and proof from ALPLA, ABB, and TGW. Learn more.
OEE Analytics on Live Data: How to Move from Nightly Exports to Real-Time Dashboards
Learn why batch export architectures make OEE dashboards too slow for shift supervisors, and how manufacturing teams cut query times from 3 to 5 minutes to milliseconds with a real-time analytics database
Data Historian vs. Time Series Database: Which Belongs in Your Industrial Stack
Compare data historians and time series databases on OT connectivity, query language, and analytics depth. Learn why most industrial stacks benefit from both.
The InfluxDB Cardinality Problem: Why High-Cardinality Industrial Data Breaks It
Learn why InfluxDB's TSM storage model hits a cardinality wall at industrial scale, and how CrateDB stores 900 sensor types in a single table without a series ceiling.
The New Industrial Data Stack: Managing Billions of IoT Events in Real Time
Managing billions of IoT events requires a new data architecture. Discover how CrateDB enables real-time analytics for industrial systems.
Why Industrial IoT Data Breaks Traditional Databases
Discover why traditional databases struggle with industrial IoT data and how CrateDB's architecture addresses challenges like velocity, schema changes, and high cardinality.
Beyond Time-Series: Why Modern IIoT Architectures Demand High-Cardinality Analytics, Flexible JSON, and Unified Observability
CrateDB enables high-cardinality IoT analytics, flexible JSON and search, edge-to-cloud IIoT, and unified machine-data observability in one distributed SQL engine.