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.
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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.
IoT Analytics: Turning Real Time Device Data into Actionable Insights
Learn what IoT analytics is, why it matters, key use cases, architecture patterns, and how to analyze real time IoT data at scale.
My AI Predictions for 2026: From Hype Cycle Reset to Structural Transformation
AI in 2026 will move beyond hype toward consolidation, cost efficiency, and real business impact. Explore key predictions shaping the next phase of artificial intelligence.
Real-Time Data Processing: What It Is, Why It Matters, and How Modern Systems Make It Possible
Real-time data processing enables systems to ingest, analyze, and act on data as it arrives. Learn how it works, key use cases, and how modern architectures support low-latency analytics at scale.