Packages:

https://gdal.org/index.html

    GDAL is a translator library for raster and vector geospatial data formats that is released under an MIT style Open Source License by the Open Source Geospatial Foundation. As a library, it presents a single raster abstract data model and single vector abstract data model to the calling application for all supported formats. It also comes with a variety of useful command line utilities for data translation and processing. 

https://libgeos.org/

    GEOS is a C/C++ library for computational geometry with a focus on algorithms used in geographic information systems (GIS) software. It implements the OGC Simple Features geometry model and provides all the spatial functions in that standard as well as many others. GEOS is a core dependency of PostGIS, QGIS, GDAL, Shapely and many others.

https://grass.osgeo.org/

    GRASS GIS offers powerful raster, vector, and geospatial processing engines in a single integrated software suite. It includes tools for terrain and ecosystem modeling, hydrology, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It comes with a temporal framework for advanced time series processing and a Python API for rapid geospatial programming. GRASS GIS has been optimized for performance and large geospatial data analysis.

https://github.com/OSGeo/libgeotiff

These have been around since the 1980s. I'm not familiar with the current state of these packages but I'm surprised that libgeotiff is distinct as I would have thought it'd fall under the umbrella of GDAL: ( https://gdal.org/drivers/raster/gtiff.html ).

Languages:

Appears to be all python shim layers and functions to leverage the packages.

Services:

Make a GIS geospatial aware database of raster data and vectors, points, pins, etc using PostgresSQL.