Real-Time Ingestion

CrateDB is designed to handle today’s relentless data velocity. Whether it’s IoT telemetry, application logs, or sensor networks, CrateDB ingests millions of events per second with horizontal scalability. Its shared-nothing architecture ensures performance grows linearly with your cluster; no bottlenecks, no single point of failure.

CrateDB connects effortlessly to your data pipelines through native integrations and open interfaces. Ingest data from Kafka, Flink, MQTT, HTTP APIs, or CDC pipelines, and keep your analytics continuously up to date. Combine structured, semi-structured, and unstructured data in a single real-time pipeline, without complex ETL.

CrateDB supports large scale batch imports from data lakes, lakehouses, cloud storage, and ETL pipelines. It loads files in formats such as CSV, JSON, Parquet, distributing and indexing them across the cluster as they arrive. This gives teams an easy path to bring historical datasets together with real-time streams in one database.

CrateDB ingests and indexes data in parallel across all cluster nodes, making every event queryable within seconds. Its built-in sharding and replication ensure resilience and instant availability, so dashboards update in real time, alerts trigger immediately, and AI models always use the freshest data.

Data in CrateDB becomes useful almost immediately, in less than one second. The ingestion path indexes each record automatically for search, aggregations, and vector operations, without manual tuning. You can run real-time analytics or feed live features into AI models within milliseconds of data arriving.

CrateDB brings ingestion, indexing, and querying together in one unified database. No separate systems to maintain or sync.

Traditional architecture	CrateDB unified approach
Separate pipeline for ingestion and storage	Single engine for ingestion + analytics
Complex ETL and schema management	Flexible schema and automatic indexing
Minutes to hours for data availability	Queryable within seconds