andygrove commented on issue #30:
URL: https://github.com/apache/arrow-ballista/issues/30#issuecomment-1146639503

   Hi @ziedbouf. I'm glad you are finding the book helpful! Let me try and 
answer some of your questions.
   
   I have not used Plasma and there is no support for it in 
DataFusion/Ballista. I recall a discussion about it being unmaintained but I 
could be wrong. Ballista doesn't provide an in-memory cache like redis, 
although it would be possible to implement a custom datasource to connect to 
redis.
   
   Ballista is similar to Spark SQL and Dask-SQL in terms of architecture, so 
yes, could be seen as a competitor although it is not as mature yet. Ballista 
does not have any stream, graph, or ML capabilities yet though. As mentioned in 
this discussion, some contributors are planning on working on streaming. 
   
   My personal view is that we need to get Ballista to the point of maturity 
where it can run industry-standard benchmarks at scale with performance and 
scalability at least as good as Spark. With that, and some better docs, the 
project hopefully starts to gain more traction and more contributors and that 
would eventually lead to people building ML features perhaps.
   
   The blaze project is really interesting because it leverages the mature 
Spark scheduler and uses DataFusion for execution.


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