[marcle]

Another relevant software category is the statistical analysis languages, including SAS, Stata and SPSS.

Old-school SAS included only two data types (floats and character strings), but allowed for SQL and sequential data-steps to live together. Persistence was baked in. The floats could be used to represent dates, datetimes and other formats. I particularly appreciated being able to use macros to define a data-step view to split the follow-up for an individual from a table. Such a view could then be collapsed using SQL. More recently, R tools such as dplyr have brought together data-frames and relational operations. However, I miss the sequential coding in SAS, using macros as higher-level tools to define the logic, including corner cases.

For strictly typed records, I have always wanted to spend more time with SML# [0] this allows for record updating, with close ties to SQL -- an under-appreciated version of SML.

[0] https://github.com/smlsharp/smlsharp