difference between t-SNE and UMAP for dimensionality reduction

The biggest difference between the the output of UMAP when compared with t-SNE is this balance between local and global structure

UMAP is often better at preserving global structure in the final projection. This means that the inter-cluster relations are potentially more meaningful than in t-SNE. However, it's important to note that, because UMAP and t-SNE both necessarily warp the high-dimensional shape of the data when projecting to lower dimensions, any given axis or distance in lower dimensions still isn’t directly interpretable in the way of techniques such as PCA.