The a==b works really well if a and b are the same, but it doesn’t tell me what’s different if a and b are different e.g. some column name are different.
I would if there’s a package for comparing dataFrame like proc compare in SAS or like pandas assert equal for data frames.
Did you set a reminder to check on this anually? 
I approximately need to do it once per year it seems.
Thought discourse would pick up the post.
I guess there isn’t exactly something I needed. So might need to create something.
Does the response from Bogumił Kamiński in SO help a bit?
It would be really nice if @ssfrr 's DeepDiffs.jl directly supported Tables.
(probably displaying via PrettyTables.jl)
But it does not
it does however support vectors
So some demos
julia> using DataFrames, DeepDiffs
julia> costs = DataFrame(brand=["BurgerDuke", "BurgerDuke", "BurgerDuke", "McDannys", "McDan
nys"], product = ["burger", "fries", "drink", "burger", "drink"], price=[10.0, 5.0, 1.0, 9.5
, 0.5])
5×3 DataFrame
Row │ brand product price
│ String String Float64
─────┼──────────────────────────────
1 │ BurgerDuke burger 10.0
2 │ BurgerDuke fries 5.0
3 │ BurgerDuke drink 1.0
4 │ McDannys burger 9.5
5 │ McDan\nnys drink 0.5
julia> costs2 = DataFrame(brand=["BurgerDuke", "BurgerDuke", "BurgerDuke", "McDannys", "McDan
nys"], product = ["burger", "fries", "drink", "burger", "drink"], price=[10.0, 7.0, 1.0, 9.5
, 0.5])
5×3 DataFrame
Row │ brand product price
│ String String Float64
─────┼──────────────────────────────
1 │ BurgerDuke burger 10.0
2 │ BurgerDuke fries 7.0
3 │ BurgerDuke drink 1.0
4 │ McDannys burger 9.5
5 │ McDan\nnys drink 0.5
by row
Perhaps best is to convert to dict:
as_dict(t) = getfield(Tables.dictcolumntable(t), :values)
