Schema relationship discovery

An apparatus for generating a schema relationship model, comprising:

• one or more memories storing processor-executable code;
• and
• one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the apparatus to:
• obtain a set of metadata associated with a plurality of entities of a datastore, the plurality of entities comprising at least two different data types;
• augment, using a generative artificial intelligence (AI) model, the set of metadata resulting in a set of augmented metadata for the plurality of entities of the datastore;
• generate, using the set of augmented metadata, a first set of entity objects for the plurality of entities of the datastore and in accordance with a reference schema, wherein generation of the first set of entity objects transforms the set of metadata associated with the plurality of entities to a common format associated with the reference schema;
• identify, using the generative AI model and the first set of entity objects as inputs into the generative AI model and based at least in part on transforming the set of metadata to the common format, one or more first relationships between two or more first entities of the plurality of entities of the datastore, wherein a first entity of the two or more first entities has a first data type of a set of data types and a second entity of the two or more first entities has a second data type of the set of data types that is different than the first data type, the set of data types comprising two or more of a structured query language (SQL) data type, a not only SQL (NoSQL) data type, a document data type, a binary large object (BLOB) data type, or a file data type;
• and
• generate the schema relationship model based at least in part on the identified one or more first relationships and in accordance with a reference schema relationship model.

A non-transitory computer-readable medium storing code for generating a schema relationship model, the code comprising instructions executable by one or more processors to:

• obtain a set of metadata associated with a plurality of entities of a datastore, the plurality of entities comprising at least two different data types;
• augment, using a generative artificial intelligence (AI) model, the set of metadata resulting in a set of augmented metadata for the plurality of entities of the datastore;
• generate, using the set of augmented metadata, a first set of entity objects for the plurality of entities of the datastore and in accordance with a reference schema, wherein generation of the first set of entity objects transforms the set of metadata associated with the plurality of entities to a common format associated with the reference schema;
• identify, using the generative AI model and the first set of entity objects as inputs into the generative AI model and based at least in part on transforming the set of metadata to the common format, one or more first relationships between two or more first entities of the plurality of entities of the datastore, wherein a first entity of the two or more first entities has a first data type of a set of data types and a second entity of the two or more first entities has a second data type of the set of data types that is different than the first data type, the set of data types comprising two or more of a structured query language (SQL) data type, a not only SQL (NoSQL) data type, a document data type, a binary large object (BLOB) data type, or a file data type;
• and
• generate the schema relationship model based at least in part on the identified one or more first relationships and in accordance with a reference schema relationship model.