Are there scientific papers that compare distributed systems and big data processing systems?
Big data processing systems can be batch processing systems or streaming big data processing systems.
A batch big data system is a distributed system that:
- loads data into the system from relational databases, log files or other sources (usually via Apache Sqoop)
- makes some computations about that data: aggregations and machine learning algorithms to train existing models or to use some models that have already been trained (via Apache Pig or Apache Spark)
- stores the result in some files or exports the data to a datawarehouse system or a relational database (using Apache Sqoop)
A streaming big data system is a distributed system that:
- has a streaming mechanism that allows messages/events to be delievered to the system (usually Apache Kafka)
- has an engine that makes elaborations on those messages, as before elaborations can include training machine learning models or using them (Apache Spark, or Apache Storm or Apache Flink)
- stores the result of elaborations or exports that result to other systems (using Apache Kafka)
What I have found so far are a lot of scientific papers about distributed systems but they don't mention streaming systems; and a lot of papers mainly empirical or marketing-oriented about big data.
The worst thing is that often, articles about big data don't mention the fact that big data systems are part of distributed systems.
Is there some material about distributed systems that explains also the systems that I have described above?