docs: add comparison with SparseArrays.jl

Author: raphasampaio

README.md

@@ -2,7 +2,7 @@
 
 [![CI](https://github.com/gcalderone/MultidimensionalSparseArrays.jl/actions/workflows/CI.yml/badge.svg)](https://github.com/gcalderone/MultidimensionalSparseArrays.jl/actions/workflows/CI.yml)
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+[![Aqua](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)
 
 A Julia package for multidimensional sparse arrays.
 
@@ -12,6 +12,16 @@ A Julia package for multidimensional sparse arrays.
 
 This package is designed to be a flexible and intuitive tool for scientific computing, data analysis, and any domain where large, sparse multidimensional data structures are common.
 
+## Comparison with `SparseArrays.jl`
+
+`MultidimensionalSparseArrays.jl` is designed to provide a flexible and easy-to-use interface for N-dimensional sparse arrays. While Julia's standard library `SparseArrays.jl` is highly optimized for 1-D and 2-D sparse arrays (vectors and matrices), `MultidimensionalSparseArrays.jl` offers a more general-purpose solution for higher-dimensional sparse data.
+
+Key differences include:
+
+- **Dimensionality:** `SparseArrays.jl` focuses on `SparseVector` and `SparseMatrixCSC`. `MultidimensionalSparseArrays.jl` is built from the ground up for N-dimensional arrays.
+- **Storage Format:** `MultidimensionalSparseArrays.jl` uses a dictionary-based storage (`Dict{CartesianIndex{N}, T}`), which is flexible for arbitrary dimensions. `SparseArrays.jl` uses the more rigid but highly efficient Compressed Sparse Column (CSC) format for matrices.
+- **Use Case:** If you are working with 1-D or 2-D sparse arrays and require high-performance linear algebra operations, `SparseArrays.jl` is the ideal choice. If you need to work with sparse data in three or more dimensions, `MultidimensionalSparseArrays.jl` provides a more natural and convenient API.
+
 ## Features
 
 - **Memory Efficiency:** Only non-zero elements are stored, making it ideal for high-dimensional sparse data.