A method begins with a processing module of a distributed storage network (DSN), receiving a request to access a data object stored in the DSN and identifying a first data descriptor associated with the data object, identifying a second data descriptor associated with the data object, identifying a first data index key and a first index structure for the first data descriptor and identifying a second data index key and a second index structure for the second data descriptor. The method continues with the processing module accessing the first index structure for the first data descriptor , based on the first and second data index keys, to retrieve a first and second set of data identifiers, respectively and based on one or more data identifiers being common to the first set of data identifiers and the second set of data identifiers, creating a superset of data identifiers.

A method for processing an unsupported data type in a database is disclosed. The method for processing an unsupported data type in a database comprises detecting, while copying data from a primary to a secondary database, a table for data comprising a data type that is unsupported by the secondary database. Furthermore, the method comprises generating a base table in the secondary database as a copy of the detected table of the primary database without the data of the unsupported data type, generating an additional table in the secondary database for data of the unsupported data type, and linking the additional table to the base table in the secondary database via a row-identifier relationship. Additionally, the method comprises accessing data of the unsupported data type via the additional table while performing queries against the secondary database.

Disclosed herein are system, method, and computer program product embodiments for storing an object onto a first or second page. An embodiment operates by receiving the object and determining that the first page has sufficient unused space for storing at least one byte of the object. Thereafter, a data block of the object is created to comprise at least one byte of the object. The data block is then stored on the first page or the second page, and a location of the object's first data block is recorded. Thereafter, a pointer corresponding to the location of the object's first data block for loading the object is provided.

Examples may include storage of a small object representation in a deduplication system. Examples may store the small object representation of an object in the deduplication system based on a determination that the object is smaller than a threshold size. In examples, the small object representation may include a direct reference from a top-level data structure to small object metadata in a bottom-level data structure of the small object representation.

This application provides a log execution method and apparatus, a computer device and a storage medium and relates to the technical field of databases. The method includes circularly scanning a log execution active window, the log execution active window comprising a plurality of logs which are not executed, and all the logs before the log execution active window having been executed; acquiring a conflict verification result of a log in the log execution active window based on storage range information of the log, the storage range information indicating a storage range of the log and a storage range of a target number of logs before the log, and the target number being equal to a size of the log execution active window; and executing the log if the conflict verification result is no conflict.

Techniques are described with respect to processing a federated query. An associated computer-implemented method includes compiling a query received from a client computing system to generate a query statement and a query access plan. The query access plan incorporates a modified database access application programming interface (API) that supports data serialization. The method further includes executing the query access plan to transmit the query statement to a remote database system. The method further includes fetching a query result set from the remote database system including serialized binary large object (BLOB) data. The method further includes deserializing the serialized BLOB data of the query result set and populating an in-memory data structure with deserialized query results. In an embodiment, the method further includes transmitting the deserialized query results to the client computing system. In an additional embodiment, the method further includes generating query serialization capabilities for the remote database system.

Techniques for indexing large scale datasets are described. A method for indexing large scale datasets can include receiving, by an indexing service, a request to generate an index for a dataset stored in an data storage service, the request including indexing information for the dataset, determining, by the indexing service, an index type based at least on the dataset, generating, by the indexing service, the index based at least on the indexing information and the index type, and receiving, by the indexing service, a request from a query service to identify a subset of the dataset using the index.

Systems, apparatuses, methods, and computer program products are disclosed for post-quantum cryptography (PQC). An example method includes receiving data. The example method further includes generating a set of data attributes about the data. The example method further includes generating a data envelope based on the set of data attributes. Subsequently, the example method includes generating an enveloped data structure based on the data envelope and the data.

A method comprises: storing, by a computing system, a relational data in a data lake; spinning-up, by an orchestration system of the computing system, an ephemeral computing node on a computing device of the computing system; importing, by the ephemeral computing node, a copy of the relational data from the data lake into a relational database management system (RDBMS) installed on the ephemeral computing node; after importing the copy of the relational data into the RDBMS, performing, by the ephemeral computing node, a computing process that runs within the RDBMS and that uses the copy of the relational data; and after completion of the computing process on the ephemeral computing node, spinning-down, by the orchestration system, the ephemeral computing node.

Creating and executing flow plans by performing at least the following: obtaining a run-time flow plan that comprises a trigger, a first operation, and a second operation, wherein the first operation precedes the second operation within the run-time flow plan and one or more input values of the second operation are linked to the first operation, determining whether one or more conditions of the trigger are met, execute the first operation based at least on the determination that the one or more conditions of the trigger are met, monitoring whether the second operation is ready for execution based at least on a determination that the one or more input values of a second action operation are ready, and executing the second action operation when the second action operation has been identified as ready for execution.