Abstract: The disclosed technologies are capable of selectively using data structure operations for path query evaluation. One technique involves reading a query that traverses at least two nodes and at least one edge of a graph in a graph database; compiling the query into a set of variables and a set of constraints, where the set of variables and the set of constraints correspond to the two nodes and the one edge of the graph; creating an in-memory data structure that comprises a table; using the set of variables and the set of constraints to determine an operation that is performable using the in-memory data structure; checking for an existence of a condition relating to the in-memory data structure or the operation; skipping the operation if the condition exists or executing the operation if the condition does not exist; and storing a set of intermediate query results in the table.

Abstract: The disclosed technologies are capable of decentralized query evaluation for a distributed graph database. In one technique, a query is divided into first and second sets of operations. The query comprises variables and constraints that correspond to at least two nodes and at least one edge of a graph in a graph database. The first set of operations for processing the query is assigned to multiple shards. A limit is communicated to the shards. The second set of operations for processing the query is executed. A list of completed operations is received from each shard. The lists of operations received from the shards are merged into a merged set of operations, which is used to determine whether query processing is finished. If query processing is not finished, then an updated limit is communicated to the shards; otherwise, query results are provided in response to the query.

Abstract: The disclosed technologies are capable of selectively using data structure operations for path query evaluation. One technique involves reading a query that traverses at least two nodes and at least one edge of a graph in a graph database; compiling the query into a set of variables and a set of constraints, where the set of variables and the set of constraints correspond to the two nodes and the one edge of the graph; creating an in-memory data structure that comprises a table; using the set of variables and the set of constraints to determine an operation that is performable using the in-memory data structure; checking for an existence of a condition relating to the in-memory data structure or the operation; skipping the operation if the condition exists or executing the operation if the condition does not exist; and storing a set of intermediate query results in the table.