Why Nussknacker?

Real-time data processing quickly becomes one of key ingredients of marketing, monitoring or fraud detection. The ability to ingest large amounts of data within (mili)seconds, to process them and draw actionable insights can become real competitive advantage.

One the most advanced platforms for stream processing is Apache Flink. It allows users to process millions of events per second and process them without losing even one. Flink offers unmatched richness of Scala/Java API for performing filtering, enrichment and sophisticated aggregations.

However, many use cases involve processes that would be best defined or changed by not-so-technical users - analysts or business people. Furthermore, many companies do not have large enough development teams to be able to define all processes with code.

This is where Nussknacker kicks in.

Flow

We strongly believe that 'zero-code' platforms are a humbug. For each deployment, some development effort is needed to define model, integrations with external systems and so on. This step includes development and produces jar with model and defined services. Read API section to learn how to define model classes and integrations.

Once those artifacts are defined and installed in Nussknacker installation, semi-technical users will be able to define specific processes using GUI.

Applications

Real-time event processing is crucial in many area. Below are sample use cases:

  • Real-time marketing
  • Fraud detection
  • Streaming ETL
  • Traffic data

results matching ""

    No results matching ""