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.
Why Most JSON Databases Fail at Real-Time Analytics
JSON databases are flexible, but many struggle with real-time analytics. Learn why performance breaks at scale and what real-time JSON analytics requires.
Distributed Databases for Real-Time Analytics: Architecture and Tradeoffs
Explore how distributed databases handle real-time analytics workloads, the architectural tradeoffs involved, and what it takes to query fresh data at scale.
High-Cardinality Database for Time Series Analytics: Why Dimensions Matter and Where CrateDB Excels
Discover how CrateDB excels in high-cardinality time series analytics, offering real-time, flexible, and scalable SQL-based solutions for modern data challenges.
How CrateDB Powers Scalable, Real-Time Analytics Backends for SaaS Companies
Discover how CrateDB enables SaaS companies to build scalable, real-time analytics backends that handle high data ingestion, complex queries, and multi-tenancy efficiently.
Distributed Search Engine: Powering Search at Scale in Modern Data Platforms
Learn what a distributed search engine is, why it matters at scale, and how search and real time analytics converge in modern data platforms.