Add links to alternatives to the readme (#1006)

* add alternatives to readme

* two more links

* tweak

* update DelimitedFiles note

Co-authored-by: Chris Elrod <[email protected]>

* load/save suggestion

* Update README.md

Co-authored-by: Chris Elrod <[email protected]>

Author: mcabbott

README.md

@@ -40,3 +40,20 @@ Contributions are very welcome, as are feature requests and suggestions. Please
 [codecov-url]: https://codecov.io/gh/JuliaData/CSV.jl
 
 [issues-url]: https://github.com/JuliaData/CSV.jl/issues
+
+## Alternatives
+
+There are several other packages for reading CSV files in Julia, which may suit your needs better:
+
+* The standard library contains [DelimitedFiles.jl](https://docs.julialang.org/en/v1/stdlib/DelimitedFiles/), at least until Julia 1.8.
+  This returns a `Matrix` rather than a [Tables.jl](https://github.com/JuliaData/Tables.jl)-style container, thus works best for files of homogenous element type. 
+  On large files, CSV.jl will be much faster.
+
+* [CSVFiles.jl](https://github.com/queryverse/CSVFiles.jl) uses the [FileIO.jl](https://github.com/JuliaIO/FileIO.jl)'s `load` / `save` API,
+  but otherwise has similar goals. Like CSV.jl, it works with [Tables.jl](https://github.com/JuliaData/Tables.jl objects such as DataFrames.
+
+* [DLMReader.jl](https://github.com/sl-solution/DLMReader.jl) also aims to be fast for large files,
+  closely associated with [InMemoryDatasets.jl](https://github.com/sl-solution/InMemoryDatasets.jl).
+
+* [Pandas.jl](https://github.com/JuliaPy/Pandas.jl) wraps Python's [pandas](https://pandas.pydata.org) library (using [PyCall.jl](https://github.com/JuliaPy/PyCall.jl)).
+  This is a closer cousin of [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl), but builds in the ability to read/write CSV files.