Works SQL
Many excellent complex event processing solutions exist to bring SQL queries to real-time event streams. Confluent's KSQL is certainly one of them.
All these solutions focus on a certain part of data processing spectrum.
What if you want to combine data aggregation, grouping and filtering with a trained machine learning model in the same data pipeline?
Works SQL supports queries for data in motion and at rest. It contains a standardized pipeline plugin and enables to leverage Apache Spark SQL queries in combination with any other of the 200+ code-free plugins.
Works Rules
Deep learning and machine learning capabilities to answer complex questions seem to lead to a complete replacement of business rule applications.
Nowadays business rules seem to be outdated, but what if you just need to check the existence of predefined conditions, say cyber threat signatures or materialized characteristics of anomalies, and append a certain score to a real-time event?
The application of business rules can respond to this use case without having to provide any machine learning capabilities.
Works Rules brings Drools rule engine to data in motion and at rest. It contains a standardized pipeline plugin to apply declarative sets of business rules to derive new facts from existing observations.
Again, this plugin can be seamless combined with any other of the 200+ code-free plugins.