Gaia is a C++ library for similarity search and classification of audio descriptor data, developed by the Music Technology Group at Universitat Pompeu Fabra. It provides a rich set of algorithms for transforming and analyzing feature collections: normalization, PCA, RCA, SVM training/prediction, feature selection, and cleaning. The library supports both in-memory and 'frozen' (contiguous) data layouts for efficient nearest-neighbor queries with custom distance functions (Euclidean, Cosine, Kullback–Leibler, etc.) and a custom filter language for WHERE-clause predicates. Python bindings via SWIG expose the full API, and a suite of command-line tools (gaiamerge, gaiainfo, gaiafreeze) handle dataset management. A built-in classification framework with scripts for SVM grid search, cross-validation, and confusion-matrix generation complements the library. Although designed for music information retrieval (MIR) workflows in conjunction with Essentia audio extractors, the library could be adapted to any domain requiring distance-based search and transformation pipelines on structured point data. The codebase is predominantly an application-level library, with a strong research flavor due to its MIR focus.