Embodiments autonomously test a logical model for inconsistencies. For example, metadata descriptive of a logical model can be received, where the logical model includes an abstraction for a database schema, the database schema is implemented at a database, and the database schema includes a fact table and a dimension table. Logical queries can be automatically generated including at least first and second logical queries based on the retrieved metadata, where the first and second logical queries target a logical object of the logical model. At least the first and second logical queries can be issued to a server that hosts the logical model, where, at the server, the first and second logical queries are translated to first and second database queries, and the first and second database queries target at least a fact table and a dimension table from the database schema. Query results received from execution of the first and second database queries can be compared. Inconsistencies can be identified when the comparison of the query results does not meet a criterion.

Systems and methods for managing a highly available distributed hybrid database comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: receive a query from a user device to retrieve data from a distributed database comprising a source node, a first plurality of replica nodes, and a second plurality of replica nodes, wherein the source node and the first plurality of replica nodes form a transactional cluster, and wherein the second plurality of replica nodes forms an analytical cluster; determine whether to process the query using the transactional cluster or the analytical cluster based on one or more rules; translate the query into a first protocol that the determined cluster comprehends; select a replica node corresponding to the determined cluster; process the query using the selected replica node; and send data associated with results from processing the query to the user device.

Methods, systems, and devices for data processing are described. Some database systems may support differential privacy for encrypted data. For example, a database may store user data as ciphertext. A system may receive a statistical query for the user data and may identify a relevant differential privacy mechanism. The system may transform the query to operate on encrypted data while including a noisification function based on the mechanism. The system may execute the transformed query at the database, involving adding noise to the query result according to the noisification function without decrypting the data. For example, the system may leverage homomorphic encryption techniques to inject the noise while the data remains encrypted. The database may return the noisified, encrypted query results, which the system may decrypt for statistical analysis. By applying differential privacy on the encrypted data, the system may avoid exposing any private user information throughout the process.

Embodiments of the invention are directed to a system, method, or computer program product for multimodal and distributed database system structured for dynamic latency reduction. In this regard, the invention comprises a unified data layer structured to map a plurality of data storage mechanisms to a common abstraction and a query engine structured for heterogenous domain based data extraction without requiring input of schema-based queries. In some embodiments, the invention comprises determining (i) one or more data components and (ii) one or more associated data domains associated with the first domain-based query by parsing the user input based on derived metadata from data dictionaries associated with a unified data layer system component. Moreover, the invention is configured to extract stored data from each of a plurality of databases based on the associated one or more data domains.

The current document is directed to graph databases and, in particular, to improvements in the operational efficiencies of, and the range of functionalities provided by, graph databases. One currently disclosed improvement provides for associating user-defined and developer-defined functions with node and relationship entities stored within the graph database. These entity-associated functions are executed in entity-associated execution environments provided to the entities during query execution. Another currently disclosed improvement provides text-replacement-based preprocessing of graph-database queries for increased clarity and for increasing the speed and accuracy with which the queries can be formulated.

Embodiments autonomously test a logical model for inconsistencies. For example, metadata descriptive of a logical model can be received, where the logical model includes an abstraction for a database schema, the database schema is implemented at a database, and the database schema includes a fact table and a dimension table. Logical queries can be automatically generated including at least first and second logical queries based on the retrieved metadata, where the first and second logical queries target a logical object of the logical model. At least the first and second logical queries can be issued to a server that hosts the logical model, where, at the server, the first and second logical queries are translated to first and second database queries, and the first and second database queries target at least a fact table and a dimension table from the database schema. Query results received from execution of the first and second database queries can be compared. Inconsistencies can be identified when the comparison of the query results does not meet a criterion.

Techniques to process a query and perform a join of tables that are distributed across nodes of a network. The join can be performed by analyzing a Where clause. An active flag structure can have flag values that identify table entries satisfying criteria of the Where clause. Keys of surviving entries of a first table can be used to generate a request for a second table to be joined. The request can be for second flags for the second table when the Where clause has criteria for the second table. A response can be used to update the first flags to change a first flag to False. After updating, data can be retrieved for first flags that are True. Requests can use identifiers associated with the first table that identify a location for sending the request, e.g., using RDMA or MPI.

There is provided a computerized method and system of data management using extended Structured Query Language (SQL). The method includes executing an extended SQL script created in response to a data query request and comprising at least one operator of: a first operator embedding a SQL statement, or a second operator embedding a named entity. The executing comprises identifying the at least one operator in the extended SQL script; for each of the at least one operator, evaluating the embedded content thereof in runtime to dynamically generate SQL code based on a runtime input; replacing each of the at least one operator and the embedded content thereof in the extended SQL script with the generated SQL code thereof, giving rise to a standard SQL script; and running the standard SQL script to obtain a processing result of the data query request.

Methods, systems, and computer-readable storage media for automatic index creation for relational database systems. Query statements from a relational database are processed to generate query patterns from the query statements. Vectorization of the query patterns is performed to transform each query pattern into a numerical vector. A clustering algorithm is executed to cluster the numerical vectors into multiple clusters. Each cluster has a respective cluster center. A frequent query pattern is determined, for at least some of the multiple clusters, that corresponds to a respective cluster center. Active columns in the frequent query patterns are determined and a database index is automatically created for each active column that does not currently have a database index.

Systems, methods, and devices are described for performing scalable data processing operations. A queue that includes a translatable portion comprising indications of data processing operations translatable to data queries and a non-translatable portion comprising indications of non-translatable data processing operations is maintained. A determination that a first data processing operation of a first code block statement is translatable to a database query is made. An indication of the first data processing operation is included in the translatable portion of the queue. Responsive to a determination that a second data processing operation of a second code block statement is undeferrable, the translatable portion of the queue is compiled into a database query. An execution of the database query to be executed by a database engine to generate a query result is caused. A result dataset corresponding to the query result is transmitted to an application configured to analyze the result dataset.