Distributed SQL database for real-time analytics and AI workloads.
Need a unified platform to ingest and query diverse data types without managing multiple disparate database systems.
Require high-throughput ingestion and real-time analytics for massive streams of sensor and time-series data.
Need fast, scalable access to structured and semi-structured datasets for training and inference pipelines.
The distributed nature of the architecture introduces unnecessary complexity and overhead for simple, low-traffic applications.
While powerful for analytics, it is not optimized for high-frequency ACID-compliant transactional workloads compared to traditional RDBMS.
AI-powered tools that can replace or augment CrateDB
CrateDB offers an open-source version alongside a managed cloud service, providing a flexible pricing model that scales based on compute and storage consumption rather than rigid per-seat licensing.