Migrating from InfluxDB to CrateDB: The Telegraf Output Plugin Swap
In this post, I am going to show you how to set up Telegraf and have it send metrics data to CrateDB.
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.
New release: CrateDB 6.3
CrateDB 6.3 enhances compatibility with SQL and PostgreSQL, unifies object store access, and improves resilience, making integration with third-party tools easier.
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.
What Are the Best Databases for Real-Time Analytics on High-Velocity IoT and Sensor Data?
Discover the best databases for real-time analytics on high-velocity IoT and sensor data, focusing on ingestion, scalability, and AI-ready pipelines.
New release: CrateDB 6.2
Discover the latest CrateDB 6.2 features that enhance PostgreSQL compatibility, operational maturity, and performance. Explore new schema management, UUID datatype, and improved SQL compatibility.
Why Time Series Data Without Context Is Just Noise
Context transforms time series data into actionable insights. Discover how integrating metrics with metadata overcomes common analytics challenges and enables real-time, intelligent decision-making.