Merging two files on multiple criteria and imperfect matching?

[Daniel Ram]

Hi, I have two data files I want to merge. The issue is I don't have an ID column shared by both files. Instead, I want to merge based off other criteria like matching email addresses.
How could I merge with the following rules:
if two email addresses match, the records match.
Otherwise, if the name and date of birth match, it's a match.

Also, how could I account for differences in names such as "David" and "Dave"?
Would the merge command work in this situation?

[Mike Lacy]

There are various community-contributed programs for this purpose. One that comes to mind is -reclink- (ssc describe reclink).

[Anders Alexandersson]

The -merge- command could be called multiple times to handle different scenarios of exact matches. Other user-written Stata programs to consider are
-reclink2-, -matchit-, and -dtalink-. If the datasets are large (say, over 100,000 observations) I usually prefer the R package -fastLink-, which you can call from Stata. How large are the two datasets? How important to you are missed matches versus false matches?

[Leonard Scott]

On this conversation, I have seen different descriptions comparing -matchit- and -reclink2-. I saw one presentation on -dtalink-.
Some of the materials are pretty complex, but would you be able to give even a brief overview on when you would use one of these vs the other and which is better for what type of tasks?
I know if was mentioned regarding large observations using an R package, but if I am better at working with Stata, using large data sets, (~500,000 observations), would it still be ok to use one of these for similar fuzzy matching work?

Thanks!