Embodiments perform string similarity analysis by receiving candidate strings of a collection to be searched and transforming each candidate string into one or more features. Embodiments generate a feature index that maps each of the features to one or more candidate strings which include the features, and transform the feature index into a low-memory index by byte encoding a sorted integer array into an encoded byte array. The transforming into a low-memory index further includes hashing each feature to an integer value and storing using a tightly-packed map a hashed value to feature identification (“ID”) mapping, using a first tightly-packed list to map each of the feature IDs to one or more candidate strings which include the features, and using a second tightly-packed list to store the feature IDs.