Systems and methods for versioning a graph database

A method comprising:

• processing, by computing hardware, data found in a first data source comprising a new version of the data using a machine-learning model to identify an applicable schema from a plurality of schemas in which each schema of the plurality of schemas corresponds to a graph representation found in a graph data structure;
• parsing, by the computing hardware, the first data source to identify a difference between the first data source and a second data source comprising a previous version of the data, wherein the difference comprises at least a data update, a data deletion, or a data addition;
• generating, by the computing hardware, a change set from the identified difference comprising a first query for the difference based on the applicable schema to implement a version update to the graph representation found in the graph data structure corresponding to the applicable schema, wherein the version update comprises at least one of a new node, a new edge, a deleted node, a deleted edge, an updated node, or an updated edge of the graph representation found in the graph data structure corresponding to the applicable schema;
• causing, by the computing hardware and responsive to detecting an issue in a prior change set of a change set repository, a rollback of the prior change set, such that the change set can correct the issue upon migration;
• saving, by the computing hardware, the change set in the change set repository;
• querying, by the computing hardware, the change set repository to retrieve an unapplied change set;
• determining, by the computing hardware, an applicable modification to make to the graph representation by utilizing an additional machine-learning model to analyze data of the graph representation and the unapplied change set from the identified difference;
• and
• providing, by the computing hardware, a second query to migrate the unapplied change set into the graph representation found in the graph data structure corresponding to the applicable schema by modifying the graph representation found in the graph data structure corresponding to the applicable schema based on the determined applicable modification.

A system comprising:

• a non-transitory computer-readable medium storing instructions;
• and
• a processing device communicatively coupled to the non-transitory computer-readable medium, wherein, the processing device is configured to execute the instructions and thereby perform operations comprising:
• conducting a plurality of iterations, wherein an iteration of the plurality of iterations comprises validating a first data source comprising a new version of data based on a schema from a plurality of schemas in which each schema in the plurality of schemas corresponds to a graph representation found in a graph data structure;
• identifying, based on the plurality of iterations, an applicable schema from the plurality of schemas;
• parsing the first data source to identify a difference between the first data source and a second data source comprising a previous version of the data, wherein the difference comprises at least a data update, a data deletion, or a data addition;
• generating a change set from the identified difference comprising a first query for the difference based on the applicable schema to implement a version update to the graph representation found in the graph data structure corresponding to the applicable schema, wherein the version update comprises at least one of a new node, a new edge, a deleted node, a deleted edge, an updated node, or an updated edge of the graph representation found in the graph data structure corresponding to the applicable schema;
• causing, by the computing hardware and responsive to detecting an issue in a prior change set of a change set repository, a rollback of the a prior change set, such that the change set can correct the issue upon migration;
• saving the change set in the change set repository;
• querying the change set repository to retrieve an unapplied change set;
• determining an applicable modification to make to the graph representation by utilizing a machine-learning model to analyze data of the graph representation and the unapplied change set from the identified difference;
• and
• providing a second query to migrate the unapplied change set into the graph representation found in the graph data structure corresponding to the applicable schema by modifying the graph representation found in the graph data structure corresponding to the applicable schema based on the determined applicable modification.