Real-Time Streaming
Ingest, process, and act, instantly.
Process high-velocity streams of data in real time and convert signals into immediate action.
From data flow to decision in one continuous system
Streaming systems often require separate ingestion, processing, and analytics layers. MonkDB unifies them into one engine.
What MonkDB makes possible for real-time streaming
Continuous ingestion of events, logs, and signals
Kafka, MQTT, CDC, S3, OPC UA, native, no broker required.
Instant querying and aggregation on incoming streams
Streaming SQL with sub-millisecond write-to-query latency.
Real-time detection of patterns and anomalies
Vector and rule-based detection on live event streams.
Immediate triggering of actions
Decisions trigger workflows directly inside the engine.
Three steps, one continuous loop
Continuous ingestion at line rate
Streams, events, logs, and transactions land directly in the query engine.
Detect patterns in flight
Aggregations, anomaly checks, and joins run on the live stream and historical state.
Trigger the next action
Decisions land in the systems that operate the business, not on a dashboard.
Latency dropped from minutes to single-digit milliseconds. We retired Kafka + Flink + a cache layer. Operators see live state, not a delayed projection.
- 8×Faster time-to-decision
- 3Stack tiers collapsed
- <1 msPipeline latency
More ways to put MonkDB to work, in your domain
From signal to action, in one continuous system.
Ver cómo MonkDB puede unificar su infraestructura de datos, con cero compromisos en soberanía, rendimiento o escala.
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