Graph databases offer a flexible storage of interconnected data. Due to NoSQL databases being schemaless, heterogeneous data can occur when performing data changes. Evolution is conducted through so called evolution operations like add, rename, delete, merge, copy, move or split. As a user can not foresee the results of the evolution operation neither the amount of data changes nor the possible schema violations or a relaxed schema, a system to show the impact of evolution is essential. To ensure schema conformity, we present an approach to close the gap of a schema management tool for graph databases in order to estimate and illustrate the impact of evolution on the schema level. To illustrate, explore, evolve and change the schema all required information is handled through a schema management layer. Besides extracting the schema, so called structural profiles are designed for an initial data exploration. The preview of the schema and structure profiles shows the impact of evolution on the data by comparing versions. Similar approaches and tools are already available for JSON based NoSQL databases. Moreover, the system uses an intuitive syntax to also enable the usage of graph databases for non-experts.