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Enterprise Layer Intelligence
Categories/Data Platform & Integration/Nstream
Nstream

Nstream

Founded 2015

Build real-time streaming data applications directly from event sources like Apache Kafka

You can use Nstream to build full-stack streaming data applications that process and display live event streams. The system connects directly to event brokers like Apache Kafka to feed real-time user interfaces, stateful services, and streaming APIs. Instead of relying on traditional polling mechanisms or complicated middleware layers, it uses push-based updates to trigger actions whenever fresh data arrives. This makes it practical to run instant fraud detection, monitor complex physical assets, and maintain continuous customer views at high scale with low latency.

What Nstream does

Connect live Apache Kafka topics to UI componentsModel stateful streaming entities using simple JSONStream real-time changes directly to browser dashboardsTrigger automated workflows when specific data events occurFilter live message streams by subscribing to exact entity keysEliminate database read bottlenecks with in-memory streaming stateDirect ingestion from Apache Kafka and Confluent streamsPush-based streaming APIs for immediate UI updatesStateful service modeling for millions of distinct entitiesSub-second full stack end-to-end latencyJSON configuration to create streaming endpoints rapidlyMultiplexed streaming data distribution to client applicationsBuilt-in state management without external caching layersNative compatibility with open-source SwimOS

Frequently asked

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Nstream, streaming data applications, real-time data, Apache Kafka, Confluent, stateful services, streaming APIs, real-time UI, event streaming, data streaming, SwimOS, event-driven architecture, asset monitoring, fraud detection, latency reduction