Abstract: An employee data replication system receives a request to replicate employee data hosted by a host system. At least one of: a live date corresponding to when the employee data is to be live on the enterprise system or a selection of one or more applications to be used on the enterprise system is identified. A cutoff date for the employee data is calculated based on one or more of the live date and the selection of one or more applications, the cutoff date indicating an oldest date for which the employee data is to be replicated to the enterprise system. Employee data is replicated from the host system to the enterprise system based on the cutoff date, and an indication is provided that the replication has completed.

Abstract: The present disclosure involves systems, software, and computer implemented methods for data confidentiality-preserving machine learning on remote datasets. An example method includes receiving connection information for connecting to a remote customer database and storing the connection information in a machine learning runtime. Workload schedule information for allowable time windows for machine learning pipeline execution on remote customer data of the customer is received from the customer. A determination is made that an execution queue includes a machine learning pipeline during an allowed time window. The connection information is used to connect to the remote customer database during the allowed time window. Execution is triggered by the machine learning runtime of the machine learning pipeline on the remote customer database. Aggregate evaluation data corresponding to the execution of the machine learning pipeline on the remote customer database is received and provided to a user.

Abstract: Various embodiments for a triple integration and querying system are described herein. An embodiment operates by identifying a plurality of triples corresponding to a knowledge graph, and generating a table in a database into which to import the set of triples. The table includes a subject column, a predicate column, and multiple object columns across different datatypes. Values from the triples of the knowledge graph are loaded into the table and a query is executed on the table.

Abstract: Systems and methods provide a generic factory class to determine one or more classes implementing an interface and/or derived from a base class in response to a call from an application factory class by retrieving a list of the one or more classes implementing the interface or derived from the based class, determining properties of each of the one or more classes, and return, based on the properties, a name of each of one or more of the one or more classes.

Abstract: Systems and methods include detection of changes to data of a plurality of source objects of a source system, replicating the data changes to corresponding ones of the plurality of target objects, and, during the detection of changes to data and the replication of the data changes: detecting a first change to a first source object, identifying a first maintenance event based on the detected first change; determining a first one or more solutions to resolve the first maintenance event; presenting the first maintenance event and the first one or more solutions to resolve the first maintenance event to a user; receiving an indication from the user of a first solution of the first one or more solutions to resolve the first maintenance event; and, in response to the indication, executing the first solution.

Abstract: A method may include receiving a definition of a table user-defined function (TUDF) in a graph query language. The table user-defined function may be created based on the definition. For example, the creation of the table user-defined function may include checking and compiling the definition to generate executable code associated with the table user-defined function. Upon receiving a query including a relational query language statement invoking the table user-defined function, such as a structured query language select statement, the query may be executed on at least a portion of a graph data stored in a database. The executing of the query may include calling the executable code to execute the table user-defined function included in the relational query language statement. Related systems and computer program products are also provided.

Abstract: Various examples are directed to systems and methods for operating a database management system (DBMS) in a cloud environment. An assembly worker executing at a first computing device may provide a first database protocol message generated by a process code executing at the first computing device. A translation engine executed at the cloud environment may translate the first database protocol message from a first format to a second format associated with a DBMS instance executing at the cloud environment to generate a translated first database protocol message. The translation engine may cause the translated first database protocol message to be provided to the DBMS instance and may receive, from the DBMS instance, a first reply corresponding to the translated first database protocol message. The first reply may be sent to the process code.

Abstract: A method may include determining a threshold quantity of attempts to optimistically perform a first transaction operating data stored in a database. The threshold quantity of attempts may be determined based on an expected workload of the first transaction and/or a workload at the database. The first transaction may be performed optimistically including by tracking cache lines accessed by the first transaction and detecting, based on a second transaction writing to a cache line accessed by the first transaction, a conflict between the first transaction and the second transaction. If the first transaction is not successful performed after the threshold quantity of attempts to optimistically perform the first transaction, the first transaction may be performed in a fallback mode including by acquiring a lock to prevent the second transaction from accessing a same data in the database as the first transaction. Related systems and articles of manufacture are also provided.

Abstract: A method for processing non-standardized data in a relational database may include identifying, within a sequence of operations forming a query pipeline for executing a query, a first operation ingesting a non-standardized data. In response to identifying the first operation ingesting the non-standardized data, a second operation may be inserted before the first operation. The non-standardized data may be output by a third operation preceding the first operation or a source external to the query pipeline. The second operation may serialize the non-standardized data for ingestion by the first operation, for example, by generating a relational table populated by the non-standardized data. The query may be executed by performing the sequence of operations included in the query pipeline. Related systems and computer program products are also provided.

Abstract: Methods and systems are disclosed for enumeration of trees in a database environment. Temporary copies of trees are stored in a database accelerator environment, for efficient access by software programs operating within the database layer. Multiple trees can be enumerated concurrently using level-by-level traversal. Nodes are assigned sortable indices through which a tree structure is maintained. Enumeration supports linking from a node of a parent tree to a child tree stored separately. Enumeration supports synthesizing child nodes in order to satisfy constraints on a parent node. Filtering and sorting are supported. The disclosed technology provides unexpectedly superior results, and can be applied in many fields. Variants are disclosed.

Abstract: A method includes receiving, at a search toolbar, a search query from a machine in a network. The machine has an associated machine profile for participating in the network as an entity. The machine profile includes a machine identifier and machine metadata. A query type is determined from the search query. A search context for the machine is determined using a semantic graph of the network. From a set of services for the network, one or more relevant services to respond to the search query are identified based on the query type and the search context. The search query is applied to the one or more relevant services to obtain a set of responses. A set of relevant results for the search query is determined from the set of responses. The set of relevant results is transmitted to the machine.

Abstract: The present disclosure provides techniques and solutions for defining, deploying, or using distributed neural networks. A distributed neural network includes a plurality of computing elements, which can include Internet of things (IOT) devices, other types of computing devices, or a combination thereof. At least one neuron of a neural network is implemented, for a given data processing request using the distributed neural network, on a single computing element. Disclosed techniques can manage data processing requests in the event of an unreachable computing element, such as by processing the request without the participation of such computing element. Disclosed techniques also include redefining distributed neural networks to replace an unreachable computing element.

Abstract: Techniques and solutions are described for storing and processing metadata. A target system sends a request to a source system to identify extensions to one or more specified database artefacts. The source system identifies one or more software objects that include metadata extensions to the one or more specified database artefacts and sends at least a portion of such metadata elements to the target system in response to the request. The source system can expose APIs, such as APIs in a standard format, to the target system to assist in requesting and retrieving metadata from the source system.

Abstract: Methods for using SQL statements to access an application-server-managed database are disclosed herein. In some embodiments, a user sends, either directly or indirectly (i.e., remotely) a SQL statement from an ODBC application or server, respectively, to an application server that preprocesses SQL statements for accessing data from a centralized database. The application server may have a SQL endpoint, and access to the SQL endpoint may be determined by a user's logon credentials, a user's presentation of a SAML token, or a user's presentation of a valid certificate. The application server may then parse the SQL statement and determine the user's authorization to access certain objects in the centralized database based on a SQL handler design-time configuration. A result from the statement may be sent back to the user either directly or indirectly and exposed.

Abstract: Techniques and solutions are described for defining and deploying application content. Content, such as objects, can be created in a repository defined for a first application. A package can be defined based at least in part on the objects for use in a computing environment only requiring the first application. A second package can be defined based at least in part on the objects for use in a computing environment in which both the first application and a second application are available. Content can be moved between repositories defined for a single application and repositories defined for multiple applications. Content can be added to, or removed from, a client computing system as applications available on a client computing system change.

Abstract: Computer-readable media, methods, and systems are disclosed for utilizing partition-based locking mechanisms to improve execution of overlapping data definition language (DDL) and data manipulation language (DML) operations on a partitioned database table. A first node receives a DML statement associated with a first transaction. The first node acquires a intent exclusive lock on table metadata. A second node receives a DDL statement associated with a second transaction and acquires an exclusive metadata lock on the partitioned table metadata. Next, an intent exclusive lock is acquired for the relevant partition table data on the second node and an exclusive lock on table metadata on the second node. The second transaction waits for the DML operation of the first transaction to complete. Then the first transaction is committed. Finally exclusive locks are acquired on table data and metadata and the second transaction is executed and committed.

Abstract: Techniques and solutions are described for providing flexible access to data during execution of a data access request. Multiple instances of a data artifact are created, where different instances of the data artifact provide access to different data sources having data associated with the data access request. When a data access request is executed, a particular data artifact instance can be used during execution of the data access request. In some cases, switching logic can be used to determine which data artifact instance is to be used in executing the data access request. Also described are technologies for facilitating creation of data artifact instances corresponding to a modelling artifact.

Abstract: Disclosed herein are system, method, and device embodiments for implementing semantic discovery. An embodiment operates by retrieving a plurality of entities from a database instance. A semantic graph representation of the plurality of entities is generated within a graphical user interface. Context information is received from a user. A focus node is determined from the plurality of nodes using the context information. A semantic context of the focus node is determined, wherein the semantic context includes the focus node, a subset of the plurality of nodes, and subset of the plurality of edges. Responsive to the receiving, a visual indication of the semantic context is displayed within the graphical user interface.