Abstract: Systems and methods are described for dynamically allocating memory for responding to requests. In some aspects, a thread may be obtained, where the thread includes a request to use a portion of system memory to perform a query of a database, such as a graph database. The system may determine that the portion of memory is greater than available memory of a maximum managed memory size of the system, and may block the thread until additional memory becomes available. The maximum managed memory size may be configurable, and may be less than a total memory of the system. The system may then determine, based at least in part on a change in the available system memory, that the available system memory is equal to or greater than the portion of memory to satisfy the request, and cause the system to process the thread to provide a response to the query.

Abstract: A computer-implemented method performed at least in part by a graph database configured to store at least one graph dataset. The method includes receiving a graph query configured to be performed against a machine learning model, and communicating the graph query with a machine learning system that is configured to use the machine learning model to obtain model inference results and communicate those model inference results to the graph database application. The graph database provides query results based at least in part on the model inference results to an entity.

Abstract: A computer-implemented method performed at least in part by a graph database configured to store at least one graph dataset. The method includes receiving a graph query configured to be performed against a machine learning model, and communicating the graph query with a machine learning system that is configured to use the machine learning model to obtain model inference results and communicate those model inference results to the graph database application. The graph database provides query results based at least in part on the model inference results to an entity.