Abstract: Examples of the present disclosure describe systems and methods for aliased data insertions/retrieval for key-value stores. In aspects, a data set comprising a primary key, one or more secondary keys (“aliases”), and data values may be received by a data storage system. The system may allocate an internal identifier to the primary key and store the internal identifier and the primary key in a first table. Each of the secondary keys may be used to create a key-value pair comprising the secondary key and the internal identifier. The key-value pair(s) may be stored in the first table with the corresponding primary key. The internal identifier and the data values may be stored in a second table. Subsequently, the primary or secondary key may be used to interrogate the first table for the internal identifier. The internal identifier may then be used to interrogate the second table for the data values.

Abstract: Controlling access to nodes in a relational graph at query time by using an approximate membership query (AMQ) filter and ordered queries based on historic grants or denials of access according to security context enables a more efficient querying of the relational graph while preserving access controls. Security contexts that grant or deny access to a node are stored in an associated AMQ filter and are queried according to the subject's security context in an order based on the frequency at which the security contexts have previously granted or denied access to nodes in the relational graph.

Abstract: The technology described herein protects the privacy of data stored in a knowledge graph (“graph”) by enforcing privacy policies when returning information in response to a query or other attempt to extract information from the graph and/or about the graph. In one aspect, unauthorized information is trimmed from the information output in response to a query. In other words, the privacy policy for a knowledge graph is enforced during the information extraction process. This is in contrast to other methods that attempt to enforce privacy policies at the information ingestion process or through some other service-level process after information is output from the graph. The privacy policies may be stored in a node of the graph.

Abstract: A method of maintaining a key-value store comprising a first record structure in which each key comprises an index and each value comprises a respective set of item IDs, and a second record structure in which each key comprises an item ID and each value comprises a respective item of data. Each new item ID of a group is added, starting at the root level of a tree structure: I) determining whether the current record will exceed a maximum size limit if the new item ID is included therein, and if not, including the new item ID, but II) if so, identifying a number of records at the next level of the tree structure, and applying a deterministic transformation to the item ID of the new item to determine one of the identified number of records, and repeating from I) with the determined record now as the current record.

Abstract: Examples of the present disclosure describe systems and methods for aliased data insertions/retrieval for key-value stores. In aspects, a data set comprising a primary key, one or more secondary keys (“aliases”), and data values may be received by a data storage system. The system may allocate an internal identifier to the primary key and store the internal identifier and the primary key in a first table. Each of the secondary keys may be used to create a key-value pair comprising the secondary key and the internal identifier. The key-value pair(s) may be stored in the first table with the corresponding primary key. The internal identifier and the data values may be stored in a second table. Subsequently, the primary or secondary key may be used to interrogate the first table for the internal identifier. The internal identifier may then be used to interrogate the second table for the data values.

Abstract: Controlling access to nodes in a relational graph at query time by using an approximate membership query (AMQ) filter and ordered queries based on historic grants or denials of access according to security context enables a more efficient querying of the relational graph while preserving access controls. Security contexts that grant or deny access to a node are stored in an associated AMQ filter and are queried according to the subject's security context in an order based on the frequency at which the security contexts have previously granted or denied access to nodes in the relational graph.

Abstract: In one aspect, a data item is written to a data chunk of a stream segment. The stream segment includes a stream segment header and a plurality of data chunks. A first identifier of the data item is written to the stream segment header of the stream segment. A second identifier of the data item is written to a header of the data chunk of the stream segment. In another aspect, a stream segment header of a stream segment is queried with a query identifier. The querying identifies if any of the data items in the data chunks of the stream segment have the query identifier. If any of the data items in the data chunks of the stream segment have the query identifier, the data chunks of the stream segment are queried with the query identifier to identify which data chunks of the stream segment have the query identifier.

Abstract: In one aspect, a data item is written to a data chunk of a stream segment. The stream segment includes a stream segment header and a plurality of data chunks. A first identifier of the data item is written to the stream segment header of the stream segment. A second identifier of the data item is written to a header of the data chunk of the stream segment. In another aspect, a stream segment header of a stream segment is queried with a query identifier. The querying identifies if any of the data items in the data chunks of the stream segment have the query identifier. If any of the data items in the data chunks of the stream segment have the query identifier, the data chunks of the stream segment are queried with the query identifier to identify which data chunks of the stream segment have the query identifier.

Abstract: Particular aspects of this disclosure relate to computerized systems for generating and using improved data structures and functionality to efficiently render different multiple access-controlled resources (or properties of access-controlled resources) that are part of a concept. Often times, two or more resources of a concept or properties of a resource are subject to different access controls. This adds computing complexity as to whether or not a user is granted access to the entire concept or resource, a portion of the concept or resource, or none of the concept or resources and what exactly is surfaced back to the user when there are resources or properties the user does and does not have access to. Some embodiments accordingly render an efficient composite view of concepts or resources where some resources or properties are accessible by the requesting user, while other resources or properties are not accessible by the requesting user.

Abstract: Reductions in latencies and improvements in computational efficiency when analyzing data stored in a relational graph by integrating analytical capabilities into graph queries. Instead of a user having to run a graph query and then perform analytics on the resulting subgraph via separate requests, the user is enabled to run analytics at the time the graph query is run via a single request to the database maintaining the relationship graph, which improves the computationally efficiency of analyzing relational graphs and thereby improves the functionality of the computing devices hosting the relational graphs and running the queries and analytics.

Abstract: A method comprising: storing, in a database, a list of geographical regions in which the party consents to their data being stored; receiving a request to store data of the party, wherein at least one of the data has a region-restriction that restricts the regions in which that data can be stored; determining, based on a respective region-restriction of a respective one of the data, in which of the list of regions the respective data can be stored; storing the data, wherein each respective data is stored in at least one respective storage centre associated with one of the regions according to the determination; storing, in the database, a list comprising a pointer to each respective stored data, wherein the pointer identifies the respective storage centre; receiving a request to retrieve a respective stored data; and using the pointer to route the request to the respective storage centre.

Abstract: A method comprising: storing, in a database, a list of geographical regions in which the party consents to their data being stored; receiving a request to store data of the party, wherein at least one of the data has a region-restriction that restricts the regions in which that data can be stored; determining, based on a respective region-restriction of a respective one of the data, in which of the list of regions the respective data can be stored; storing the data, wherein each respective data is stored in at least one respective storage centre associated with one of the regions according to the determination; storing, in the database, a list comprising a pointer to each respective stored data, wherein the pointer identifies the respective storage centre; receiving a request to retrieve a respective stored data; and using the pointer to route the request to the respective storage centre.

Abstract: Controlling access to nodes in a relational graph at query time by using an approximate membership query (AMQ) filter and ordered queries based on historic grants or denials of access according to security context enables a more efficient querying of the relational graph while preserving access controls. Security contexts that grant or deny access to a node are stored in an associated AMQ filter and are queried according to the subject's security context in an order based on the frequency at which the security contexts have previously granted or denied access to nodes in the relational graph.

Abstract: A method comprising: storing, in a database, a list of geographical regions in which the party consents to their data being stored; receiving a request to store data of the party, wherein at least one of the data has a region-restriction that restricts the regions in which that data can be stored; determining, based on a respective region-restriction of a respective one of the data, in which of the list of regions the respective data can be stored; storing the data, wherein each respective data is stored in at least one respective storage centre associated with one of the regions according to the determination; storing, in the database, a list comprising a pointer to each respective stored data, wherein the pointer identifies the respective storage centre; receiving a request to retrieve a respective stored data; and using the pointer to route the request to the respective storage centre.

Abstract: Controlling access to nodes in a relational graph at query time by using an approximate membership query (AMQ) filter and ordered queries based on historic grants or denials of access according to security context enables a more efficient querying of the relational graph while preserving access controls. Security contexts that grant or deny access to a node are stored in an associated AMQ filter and are queried according to the subject's security context in an order based on the frequency at which the security contexts have previously granted or denied access to nodes in the relational graph.

Abstract: Approximate Membership Query (AMQ) Filters are used in conjunction with graph queries to a relational graph to provide change monitoring that span views associated with the queries. Each node from the relational graph spanned by a graph query and the index structure for the view are added as members to an AMQ filter. When a change is made to the relational graph, the changed nodes are queried against the AMQ filter. When a changed node is noted as a candidate member of the AMQ filter, the graph query may be rerun to update the view associated with the query. Otherwise, the graph query is not rerun, thus saving computing resources and improving the systems hosting and querying the relational graph.

Abstract: Reductions in latencies and improvements in computational efficiency when analyzing data stored in a relational graph by integrating analytical capabilities into graph queries. Instead of a user having to run a graph query and then perform analytics on the resulting subgraph via separate requests, the user is enabled to run analytics at the time the graph query is run via a single request to the database maintaining the relationship graph, which improves the computationally efficiency of analyzing relational graphs and thereby improves the functionality of the computing devices hosting the relational graphs and running the queries and analytics.

Abstract: In one aspect, a data item is written to a data chunk of a stream segment. The stream segment includes a stream segment header and a plurality of data chunks. A first identifier of the data item is written to the stream segment header of the stream segment. A second identifier of the data item is written to a header of the data chunk of the stream segment. In another aspect, a stream segment header of a stream segment is queried with a query identifier. The querying identifies if any of the data items in the data chunks of the stream segment have the query identifier. If any of the data items in the data chunks of the stream segment have the query identifier, the data chunks of the stream segment are queried with the query identifier to identify which data chunks of the stream segment have the query identifier.

Abstract: Reductions in latencies and improvements in computational efficiency when analyzing data stored in a relational graph by integrating analytical capabilities into graph queries. Instead of a user having to run a graph query and then perform analytics on the resulting subgraph via separate requests, the user is enabled to run analytics at the time the graph query is run via a single request to the database maintaining the relationship graph, which improves the computationally efficiency of analyzing relational graphs and thereby improves the functionality of the computing devices hosting the relational graphs and running the queries and analytics.

Abstract: Systems, methods, and computer readable devices embodying instructions are provided herein for reducing latencies and/or improving computational efficiency when traversing data stored in a relational graph by caching subgraphs and enabling the utilization thereof. More specifically, after a user performs a graph query, the resulting subgraphs of the graph query are cached in a reusable form. Subsequent graph queries are able to identify cached subgraphs based on the graph query. Further, the subsequent graph query is operable to integrate the cached subgraphs as part of the result of subsequent graph query, which may include a portion or the entire result of the subsequent graph query being composed from cached subgraphs, thereby improving the computational efficiency and performance of querying relational graphs, reducing the query execution cost required to traverse the relational graphs, and improving the functionality of the computing devices hosting the relational graphs and running the queries.