Data-Oriented implementation and scalability

May of our components are designed used within existing enterprise environments in a data-oriented way. This means that:

• All the components accept and output human-interpretable data, often in tabular format

• The computations can be scaled by splitting and recombining data in straightforward ways

• The components can be used as part of data processing systems such as Apache Spark, various branded and enhanced Spark systems, as part of low-code tools, web-based systems using REST APIs and queue-based processing architectures

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