Abstract: Technologies are described for managing shared read-only objects in hybrid distributed database systems. For example, data structures can be maintained for managing the shared read-only objects, comprising a data structure storing a “deleted at” value for each shared read-only object, a data structure storing a “deleted at” value for each secondary node, a data structure storing a indication of which secondary nodes are reading which shared read-only objects, and a data structure storing a reference count indicating a number of active read transactions for each shared read-only object. The shared read-only objects that can be garbage collected can be identified using, at least in part, the data structures. The identified shared read-only objects can then be garbage collected.

Abstract: A computer implemented method can receive an event object published by a source entity, parse the event object to retrieve an event message pertaining to an event awaiting processing and one or more target entities authorized to process the event, identify one or more receiving entities having subscribed to the event object from the one or more target entities, create a message queue connected with one or more message routes that directly link the source entity to the respective one or more receiving entities, and post the event message to the message queue.

Abstract: Methods and apparatus are disclosed for staged query compilation. One or more intermediate plans between a query and its execution plan are stored according to a common specification for plan data structures. Data sources, a plan flow, and annotations can be stored in respective fields of the plan data structure, which can be extended with a field for a serialized execution plan. Plan data structures provide a stable interface for integration of local and external software modules, and decouple plan representation from plan optimization. Use cases are disclosed for integrating offline optimization with inline software modules, for integrating local query handling with external services, for caching intermediate plans, and for archiving plans across version changes of optimizers. A hub architecture flexibly supports numerous compilation workflows. Disclosed technologies are suitable for cloud deployments and for migration of databases into the cloud.

Abstract: Techniques and solutions are described for storing and processing metadata models using a metadata hub that can be accessed by a plurality of computing systems. The metadata hub can receive requests to retrieve or store metadata models. The metadata models can be converted between first and second formats. In some cases, the second format can be a relational format, such as a representation of a metadata model as one or more records in one or more database tables. The metadata hub can be used to compare metadata models, including comparing a metadata model provided by a client system with one or more metadata models stored in a repository maintained by the metadata hub. In at least some cases, the metadata model provided by the client system is not stored. The repository can be queried to find related metadata models, or to find metadata models meeting specified search criteria.

Abstract: Software feature metadata objects and software artifact search, identification, and tracking is provided herein. A software artifact can have an associated software feature metadata object. A software feature metadata object can include metadata describing or defining at least in part the software artifact. The software feature metadata object can include one or more defined queries for identifying the software artifact in applications or programming code. The software feature metadata object can include one or more identifiers for composite software artifacts which integrate the software artifact corresponding to the software feature metadata object. The software feature metadata object can be accessed to obtain metadata about the corresponding software artifact for tracking usage, integration, or other activities, which can be provided for reporting or analysis.

Abstract: Techniques for implementing a dynamic intelligent log analysis tool are disclosed. In some embodiments, a computer system performs operations comprising: obtaining a log file comprising a plurality of log entries, each log entry comprising an error message; identifying a set of unique words from the error messages; for each error message, computing a term-frequency vector based on a frequency of occurrence for each unique word of the set of unique words in the error message; for each error message, computing a similarity measure between the term-frequency vectors of the error message and every other error message of the log entries; for each error message, computing a score based on a sum of the similarity measures; and displaying an indication of one or more of the error messages on a computing device based on the scores for the one or more of the error messages.

Abstract: A computer-implemented method includes receiving a request of data records for a data schema, obtaining a schema alignment which maps the data schema to a subset of an ontology of a knowledge graph, generating at least one query based on the subset of the ontology of the knowledge graph, obtaining a list of data records by executing the at least one query on the knowledge graph to obtain a list of data records, and persisting the list of data records to the data schema.

Abstract: Technologies are described for establishing a connection to an IMDB (in-memory database) via a GUI, automatically detecting an IMDB version, and selecting at least one script from a plurality of scripts based on the detected IMDB version. Differences among the plurality of scripts can relate to data parameter differences in different IMDB versions. The selected at least one script to be executed returns data of a type recognized in the detected IMDB version.

Abstract: A computer implemented method can receive a request for a fallback query execution plan of a query in a database system. The query involves an object of the database system. The object is associated with a captured object. The method can evaluate whether the object and the captured object have the same logical structure. Responsive to an indication that the object and the captured object have the same logical structure, the method can reuse the fallback query execution plan to execute the query. The evaluating includes identifying a logical structure of the captured object stored in an object definition table, obtaining a current logical structure of the object, and comparing the logical structure of the captured object with the current logical structure of the object.

Abstract: Access to blockchain data may be removed by deleting an encryption key held in a remote server. Incoming data is stored in the blockchain after being encrypted at the key server. An ordinary blockchain user gains access to the data, after forwarding the encrypted data to the remote key server for decryption. Upon receipt of an input (e.g., time stamp), the key server deletes the key. Thereafter, the encrypted data on the blockchain is rendered inaccessible to the ordinary blockchain data user. At no point, does the ordinary data user have access to the key stored in the remote server. Embodiments may find particular use in removing access to personal data stored in a blockchain following the elapse of a predetermined amount of time, as may be required by privacy laws. Granular control over data access can may be afforded through the use of composite keys and/or key hierarchies.

Abstract: Implementations include querying metadata of data objects to define a sub-set of data objects, each data object in the sub-set of data objects including a generic text field and/or an attachment field, and, for each data object in the sub-set of data objects, processing historical data of a data object to identify a set of data types, the historical data stored within a field of a table of a database system, providing a recommendation for a first extension corresponding to a first data type, and receiving user input indicating acceptance of the recommendation for the first extension and, in response, automatically providing extension code that is executable to add a field extension to the table and to modify a UI of an application for input of values corresponding to the first data type, and executing the extension code to deploy the extension and to modify the UI.

Abstract: In an example embodiment, a machine learning algorithm is used to train a machine-learned model to create a three-dimensional representation of products, with each product mapped into a coordinate in the three-dimensional space. The model selects the coordinates based on the similarity of the product to other products. Coordinates that are closer geometrically in the three-dimensional space represent products that are similar to each other, whereas as the coordinates get further and further away, this implies that the products are less and less similar. This machine-learned model then not only allows for quick analysis of multiple products, as similarity between products or groups of products can be performed using geometric calculations (e.g., cosine distance), but also can then be tied into a three-dimensional representation that can be displayed either on a two-dimensional display or displayed on a three-dimensional display.

Abstract: Systems, methods, and computer-readable media are disclosed for visual labeling of training data items for training a machine learning model. Training data items may be generated for training the machine learning model. Visual labels, such as QR codes, may be created for the training data items. The creation of the training data item and the visual label may be automated. The visual labels and the training data items may be combined to obtain a labeled training data item. The labeled training data item may comprise a separator to distinguish the training data item from the visual label. The labeled training data item may be used for training and validation of the machine learning model. The machine learning model may analyze the training data item, attempt to identify the training data item, and compare the identification against the embedded label.

Abstract: Computer-readable media, methods, and systems are disclosed for minimizing data volume growth in a database system under changes to an encryption status of a plurality of data pages persisted to a database. Initially, a request is received to update an encryption parameter associated with the database. Next, it is determined whether a candidate page requires encryption changes. In response to determining that the candidate page is not currently in use by one or more active database snapshots and not currently loaded in main memory, the candidate page is loaded into main memory. Next, an encryption operation is performed on the candidate page, and the encrypted page is designated for persistence. Finally, based on a current number of candidate pages already encrypted during a current save point cycle, the selective iteration is paused until a subsequent save point cycle.

Abstract: A method may include detecting one or more trigger events at a first data center hosting a software application having a first customer onboarded at the first data center but not a second data center also hosting the software application. In response to the trigger events, a first data associated with the first customer may be replicated at the second data center to enable a collaboration between the first customer and a second customer of the software application onboarded at the second data center but not the first data center. One or more data replication relevant settings may be applied to prevent a second data associated with the first customer from being replicated at the second data center. Furthermore, the data replication relevant settings may be applied to prevent the first data from being replicated at a third data center. Related systems and computer program products are also provided.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for on-demand outage notifications in a cloud environment. Data defining statuses of network calls exchanged between web agents registered at correspondingly different network segments of a cloud platform is evaluated to determine health statuses of the cloud platform. In response to receiving a request to subscribe an application for notifications for a current health status, registering, at the health service, the application to receive the notifications associated with health statuses of network connectivity of the cloud platform. The application is registered to receive the notifications at a subscription network address under a notification regime. A notification for the current health status of network connectivity of the cloud platform is dynamically provided by the health service. The notification is provided to the registered application according to notification rules defined in the notification regime.

Abstract: In an example embodiment, when a user creates a consignment issue item for a given product in a sales order, the system will reserve/temporarily allocate the available quantity in consignment stock. A synchronous call to lock the inventor makes a tentative update to the inventory stock on the quantity required for the request product on the created issue item. This update is tentative because the locked quantity should be released if the user decides not to save the document, but it also should be locked so that it is not available to another user who is also trying to create an issue item in a different sales order document for the same product in a parallel session. The allocation may also change several times before saving the document by additional synchronous calls that again update the tentative allocations. When the user finally decides the final state of the issue item, it asynchronously sends either a confirmation or compensate message based on whether the document was saved or not saved.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for managing incompliances of application instances running in a cloud environment. Compliance requests can be generated for incompliant instances of cloud applications running on a cloud platform. In response, compliance checks for the one or more incompliant instances of cloud applications running on the cloud platform can be automatically executed. Incompliances can be identified by different compliance monitors instantiated at the cloud platform. Each compliance monitor is responsible for a particular type of incompliances. In response to identifying that a first instance of a first cloud application has a first type of incompliance, a maintenance action to be automatically executed by a first compliance maintainer running on the cloud platform is scheduled. The first compliance maintainer executes automatically a compliance measurement action for the first type of incompliance.

Abstract: A computer-implemented method includes representing a plurality of database tables as respective vectors in a multi-dimensional vector space, receiving an indication that a first database table represented by a first vector and a second database table represented by a second vector are related to each other, moving positions of the respective vectors representing the plurality of database tables in the multi-dimensional vector space in response to the indication, and grouping the plurality of database tables into one or more table clusters based on positions of the respective vectors representing the plurality of database tables in the multi-dimensional vector space.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment having an integration service (e.g., associated with a Software-as-a-Service or a Platform-as-a-Service). A design microservice may have a User Interface (“UI”) framework and UI components for a first integration developer. A configuration framework may determine a set of configuration values for an integration component of an integration scenario defined by the first integration developer. The configuration framework may then receive, from the first integration developer, a publication indication associated with the integration component. Responsive to the publication indication, the configuration framework may arrange for the set of configuration values for the integration component to be made available to a second integration developer (e.g., via a marketplace platform).