Graph databases may not be the best fit for projects that involve disconnected data with no relationships between transactions, or where optimizing for writing and storing data without querying it is a priority. They also struggle when core data objects or data models are fixed and tabular, or when large amounts of text or BLOBs need to be stored as properties. Additionally, graph databases may not excel in scenarios that involve bulk data scans or queries starting from an unknown data point. However, they can provide significant value in business-critical use cases where users want to understand relationships in their data, create well-rounded customer profiles, and perform complex analysis on connected data.