Abstract: Techniques are disclosed to manage use of a global pool of memory comprising at least a portion of the runtime-managed heap. A request to reserve use of a portion of the global pool of memory is received from each of a plurality of transactions comprising a transactional workload of a database management system. A corresponding portion of the global pool of memory is allocated to each of at least a subset of the requesting transactions, to be used as a local pool of memory available to be used by the transaction to process the transaction.

Abstract: Techniques are disclosed to provide guided natural language interactions with a connected data system, such as a graph database. In various embodiments, natural language input associated with a graph database query associated with a graph data set is received. The natural language input is processed to generate a set of candidate strings. At least a subset of the candidate strings is mapped to an entity in the graph data set. The entity and data comprising the graph data are used set to determine a candidate graph pattern associated with the graph database query. The candidate graph pattern is used to guide a user associated with the natural language input to refine the graph database query.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: A graph-based data privacy compliance solution is disclosed. In various embodiments, a privacy graph database based at least in part on an associated privacy graph model is used to store private information of a person, including by including in the privacy graph database a node representing a critical data element comprising the private information of the person.

Abstract: Techniques are disclosed to provide correctness-preserving security for graph databases. In various embodiments, security context data associated with a user with respect to a graph database is stored. A query associated with the user with respect to the graph database is received. A path is allowed to be traversed in connection with responding to the query based at least in part on a grant of a traversal right, reflected in the security context data, to traverse one or more of a node and a relationship included in the path.

Abstract: A method and apparatus for estimating the cardinality of graph pattern queries using graph statistics and metadata is presented. In various embodiments, node and edge labels are used to compute estimates for graph patterns (bi-grams) and the estimates for these patterns as composed to provide cardinality estimates of longer paths. The computation of bi-grams is low cost and requires only minimal changes to the existing query planner in the existing database machinery to be useful. The resulting estimates are used during query execution to minimize the amount of work needed to complete a query and return a faithful and accurate answer to the user. The apparatus includes modules containing computer-executable instructions to perform the above method.

Abstract: A database system with a transactional commit protocol based on a safe conjunction of majorities is disclosed. In various embodiments, a directed acyclic graph comprising, for each of a plurality of database transactions, data identifying the transaction, data indicating one or more prior database transactions on which the database transaction depends, and data indicating whether the transaction has been committed is stored. A leading edge comprising a set of committed leaf nodes of the directed acyclic graph is determined. Data representing the leading edge is provided to a transaction coordinator configured to use the leading edge to determine based at least in part on the leading edge to commit a transaction.

Abstract: Techniques are disclosed to provide a graph based recommendation system. A recommendation engine definition that includes for each of a plurality of pipeline phases a corresponding phase definition and data indicating a location of the phase in a pipeline defined by the recommendation engine definition is stored in a memory of other storage device. The recommendation engine definition is used to generate programmatically one or more procedures to provide a recommendation engine that implements the pipeline. An API usable by a client to obtain a recommendation from the recommendation engine is generated programmatically and exposed.

Abstract: A method and apparatus for estimating the cardinality of graph pattern queries using graph statistics and metadata is presented. In various embodiments, node and edge labels are used to compute estimates for graph patterns (bi-grams) and the estimates for these patterns as composed to provide cardinality estimates of longer paths. The computation of bi-grams is low cost and requires only minimal changes to the existing query planner in the existing database machinery to be useful. The resulting estimates are used during query execution to minimize the amount of work needed to complete a query and return a faithful and accurate answer to the user. The apparatus includes modules containing computer-executable instructions to perform the above method.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: Techniques are disclosed to provide correctness-preserving security for graph databases. In various embodiments, security context data associated with a user with respect to a graph database is stored. A query associated with the user with respect to the graph database is received. A path is allowed to be traversed in connection with responding to the query based at least in part on a grant of a traversal right, reflected in the security context data, to traverse one or more of a node and a relationship included in the path.

Abstract: A database system with a transactional commit protocol based on a safe conjunction of majorities is disclosed. In various embodiments, a directed acyclic graph comprising, for each of a plurality of database transactions, data identifying the transaction, data indicating one or more prior database transactions on which the database transaction depends, and data indicating whether the transaction has been committed is stored. A leading edge comprising a set of committed leaf nodes of the directed acyclic graph is determined. Data representing the leading edge is provided to a transaction coordinator configured to use the leading edge to determine based at least in part on the leading edge to commit a transaction.

Abstract: A method and apparatus for estimating the cardinality of graph pattern queries using graph statistics and metadata is presented. In various embodiments, node and edge labels are used to compute estimates for graph patterns (bi-grams) and the estimates for these patterns as composed to provide cardinality estimates of longer paths. The computation of bi-grams is low cost and requires only minimal changes to the existing query planner in the existing database machinery to be useful. The resulting estimates are used during query execution to minimize the amount of work needed to complete a query and return a faithful and accurate answer to the user. The apparatus includes modules containing computer-executable instructions to perform the above method.

Abstract: Techniques are disclosed to provide a graph based recommendation system. A recommendation engine definition that includes for each of a plurality of pipeline phases a corresponding phase definition and data indicating a location of the phase in a pipeline defined by the recommendation engine definition is stored in a memory of other storage device. The recommendation engine definition is used to generate programmatically one or more procedures to provide a recommendation engine that implements the pipeline. An API usable by a client to obtain a recommendation from the recommendation engine is generated programmatically and exposed.

Abstract: Techniques are disclosed to safely and performantly store data in a distributed graph database. In various embodiments, a combination of a replication protocol for data redundancy with a chain-commit protocol is used to ensure a safe ordering of concurrent updates across servers. The resulting protocol allows a distributed graph database to simultaneously uphold ACID properties and a useful degree of scalability through concurrent processing of updates in the typical case, and serialization of updates only where data integrity would otherwise be at risk.

Abstract: Techniques are disclosed to provide guided natural language interactions with a connected data system, such as a graph database. In various embodiments, natural language input associated with a graph database query associated with a graph data set is received. The natural language input is processed to generate a set of candidate strings. At least a subset of the candidate strings is mapped to an entity in the graph data set. The entity and data comprising the graph data are used set to determine a candidate graph pattern associated with the graph database query. The candidate graph pattern is used to guide a user associated with the natural language input to refine the graph database query.