Large amount of timecourses in database
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I have a rather large amount of data (~400 mio datapoints) which is organized in a set of ~100,000 timecourses. This data may change every day and for reasons of revision-safety has to be archived daily.

Obviously we are talking about way too much data to be handled efficiently, so I made some analysis on sample data. Approx. 60 to 80% of the courses do not change at all between two days and for the rest only a very limited amount of the elements changes. All in all I expect much less than 10 mio datapoints change.

The question is, how do I make use of this knowledge? I am aware of concepts like the Delta-Trees used by SVN and similar techniques, however I would prefer, if the database itself would be capable of handling such semantic compression. We are using Oracle 11g for storage and the question is, is there a better way than a homebrew solution?