We believe that streaming data is going to be a huge focus for businesses over the coming years, with more companies moving away from batch business intelligence and analytics towards processing streams of real time data and responding to situations in real time. This is evidenced by the growth of Kafka and Confluent as a fabric for supporting real time event based architecture.
Unfortunately, the tools for moving towards real-time and streaming analytics are still very complex to use. Whereas business analysts have SQL at their disposal, people writing streaming analytics have to use lower level libraries such as Flink or Kafka Streams which are accessed through programming languages. Writing stream processing code is very complex, with strange idioms and patterns and considerable complexity in implementing something like a stream to stream join.
Timeflow SaaS has been developed as a low code alternative to platforms such as Flink and Kafka Streams, allowing us to develop and deploy stream processing logic in a web based GUI, with no code to write. It allows us to listen to streams of data, and perform filtering, aggregations and calculations of metrics as data streams in, and then expose both the original data and derived data through various reporting and analytical front-ends. Crucially, Timeflow SaaS also allows us to identify situations of interest and route them for either automated or manual resolution.
To bring this to life, please visit the demonstration videos below. If you would like to discuss, please get in touch for an informal conversation.