Apache Kafka

Is SQL good enough?

While SQL is a widely recognized and valuable tool for data processing, it often falls short when tackling the complexities of modern Kafka streaming processing applications.

When SQL reaches its limits in Kafka stream processing

• complex business logic: multi-step transformations can grow into thousands of lines, becoming hard to maintain,
• error handling and recovery: lacks of native support for retries, compensating actions, or dead-letter queues,
• stateful processing: managing state across events, such as sessionization or pattern detection, exceeds simple syntax,
• external integrations: connecting to APIs or external systems requires capabilities beyond standard SQL,
• performance tuning: optimizing resource-heavy operations in real-time requires fine-grained control,
• flexibility: adapting to evolving requirements in a fast-moving environment can be challenging with SQL's rigid structure.

Nussknacker is a low-code platform for building, deploying, and managing real-time data processing workflows. It simplifies complex stream processing by offering an intuitive drag-and-drop interface, eliminating the need for extensive coding.

With native support for Apache Kafka & Flink, real-time events can be enriched using REST APIs, database lookups and ML inference. Nussknacker enables teams to quickly create and adapt business logic, ensuring scalability and efficiency in handling dynamic data streams.

ML model deployment & inference

Infer machine learning models in real time from complex decision algorithms
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Internet of Things

Automating actionable data in
- predictive maintenance
- inventory management
- smart devices
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Feature engineering pipelines

Streamline the creation and transformation of data features for machine learning models with Nussknacker.