What querying capabilities does ml-metadata provide

The list of "Functionality Enabled by MLMD" implies the ability to query MLMD. For example "List all Artifacts of a specific type", "query context of workflow runs", and "Show a DAG of all related executions and their input and output artifacts of a context" described by [Functionality Enabled by MLMD](https://github.com/google/ml-metadata/blob/master/g3doc/get_started.md) From the API, I am unclear how to accomplish this functionality without interacting directly with the database which does not conform to your design.

Could you provide examples of how to achieve this functionality?

Specifically, I would like to identify artifacts, executions events, or context through a query of their properties and then retrieve related context, executions and contexts related by the directed acyclic graph (DAG) related to the queried results.

Is this possible? How can it be achieved through the API?

metadata_store.py provides the ability to retrieve an entire list (e.g. get_executions) or a single item (e.g. get_contexts_by_id) but I am unclear how to achieve the stated ml-metadata through this interface.