In various aspects of the present disclosure, systems and methods are described to identify and resolve structured queries so they execute consistently and accurately against any data architecture, and for example, dynamic or unstructured database stores. According to one embodiment, a dynamic schema data system implements a query dialect that is configured to expose underlying flexible schemas of the dynamic schema data system, any structured data, unstructured or partially structured data, and expressive querying native to the dynamic schema system in a language that is compatible with structured queries, and for example, compatible with SQL-92. In further embodiments, the query dialect is configured to enable consistency with existing dynamic schema database query semantics (e.g., the known MongoDB database and associated query semantics).

A unified graph query system provides an abstraction layer that increases the interoperability of different graph technologies by exposing graphs stored in graph databases using a unified query language. The abstraction layer generates graph models for each of the available graph databases and extracts a graph component and other source data used to identify the source of the data requested by a query. The unified graph query system executes the query across the multiple graphs included in different graph databases by using the graph models to locate the graph component in each of the multiple graphs and extract the feature data associated with the graph component. The feature data is used to generate features that are used by a machine learning service to train machine learning models and is also used to make predictions in real time.

The present disclosure involves computer-implemented method, medium, and system for automatically correlating semantically connected data and metadata. One example method includes identifying a document that is to be analyzed using a semantics based mapping (SBM) infrastructure. A matching process is performed for the identified document using the SBM infrastructure, where the matching process identifies a plurality of matching terms within the document, the plurality of matching terms are assigned to a plurality of semantics identifiers (IDs), and each semantics ID corresponds to one or more terms in the plurality of matching terms. Each of the plurality of matching terms is replaced with a respective term ID to generate an updated document. A request to search for a target term in the document is received. The target term is translated to a target term ID based on the SBM infrastructure. The updated document is searched for one or more matching terms.

In some embodiments, a method receives a connection to a data source. The method analyzes metadata of the data source to determine a first type of metadata for a first type of database access and a second type of metadata for a second type of database access. The first type of metadata and the second type of metadata are combined into a data structure. Then, the method stores the data structure where the data structure is used to analyze a query to determine which of the first type of database access and the second type of database access to use for the query.

Systems and methods for querying a database are disclosed. A server computing device includes a processor and a memory storing instructions that, when executed by the processor, cause the server computing device to: receive a query input from a client device over a network connection; establish a non-blocking socket between the client computing device and the server computing device; generate a database query based on the query input; cause the database query to begin executing against one or more databases; perform a read request on the non-blocking socket; receive a code in response to the read request on the non-blocking socket; determine whether the network connection exists between the client device and the server device based on the received code; and cause the database query to be cancelled when the server determines that the network connection does not exist between the client device and the server device.

The improved exercise of artificial intelligence by providing a systematic way for a computing system to interface with output from AI models. To do this, the computing system obtains results of an input data set being applied to an AI model. The results are then refined based upon characteristic(s) of the AI model and perhaps the input data set. Based upon characteristic(s) of the AI model and perhaps the input data set, interface element(s) are identified that can be used to interface with the refined results. The interface element(s) are then communicated to an interface element that interfaces with the refined results. The interface element(s) may include, for instance, operator(s) or term(s) that may be used to query against the refined results and/or an identification of visualization(s) that may be used to present to a user results of queries against the refined results.

A data server may support segment identification based on a selected user profile. For example, a user may select a user profile as the basis for identifying a segment of additional user profiles. The server may identify attributes associated with the selected user identifier and generate an expression based on the identified subset. The expression may include a normalization function corresponding to at least one attribute. The normalization function may identify correlated attribute values for an attribute associated with the selected user profile. The data server may query a data storage system to identify the additional user profiles based on the expression. The data server may also support user defined Boolean expressions such that the expression is used to identify user identifiers associated with a first attribute and a second attribute.

A method for providing optimized support for transactional processing and analytical processing with minimal memory footprint may include storing, on a data page in a disk of a database system, a portion of one or more columns of data from a database table. A metadata associated with the data page may be stored on a metadata page in the disk of the database system. The metadata may include one or more byte ranges on the data page at which the portion of the one or more columns of data is stored. The database system may execute one or more queries by accessing, based at least on the metadata associated with the data page, a portion of the data page storing the portion of the one or more columns of data required by the one or more queries. Related systems and articles of manufacture are also provided.

Methods, systems, and computer-readable storage media for receiving, by a current database system, a query plan file representative of a captured query plan from a source database system, receiving, by the current database system, a set of definitions including one or more definitions, each definition in the set of definitions corresponding to an object that is implicated by the query plan, the object being included in a set of objects, and determining, by the current database system, that each definition in the set of definitions is identical to a respective definition of a corresponding object within the current database system, and in response: executing the captured query plan in the current database system to provide a query result.

Described are methods, systems and computer readable media for dynamic updating of query result displays.