A code generator platform may receive source metadata and a target data model. The code generator platform may determine a parameter, of the target data model, that is associated with the attribute. The code generator platform may map, based on the attribute and the source metadata, the data to the parameter of the target data model. The code generator platform may generate, based on mapping the data to the parameter, data transformation code associated with the data and the target data model, wherein the data transformation code, when executed, generates target data that corresponds to the data according to the target data model. The code generator platform may perform an action associated with the data transformation code to permit the data transformation code to be executed in order to update a target database with the target data.

Techniques are disclosed relating to determining whether a set of database schemas are different. A computer system may receive a request to create a snapshot for a set of data stored in a database having a first database schema. In response to receiving the request, the computer system may create the snapshot for the set of data. As part of the creating, the computer system may generate, based on the first database schema, a first hierarchy of hash values that includes a first root hash value for the first database schema. The first hierarchy of hash values may be usable to determine whether the first database schema is different from a second database schema. The computer system may include the first hierarchy of hash values with the snapshot.

Embodiments of the present disclosure provide an enhanced method of discovering shared objects that utilizes share authorization in addition to role authorization when a role is attempting to discover shared objects. A consumer account may invoke an operation referencing shared objects within a provider account using an imported database as a current session database. In response, a call context of the operation may be updated to save the imported database as a current session database and the imported database may be mapped to a first share and to a shared database. A first authorization based on whether the role has access privileges to the shared objects may be performed. The shared database may be used to identify schemas and the schemas may be used to identify shares associated with the imported database. A secondary authorization may be performed based on permissions that the shares associated with the imported database have on the shared objects.

Systems and methods discussed herein, based on a key-value data store including multiple-tiered sorted data structures in memory and storage, implement granularly timestamped concurrency control. The multiple-tiering of the key-value data store enables resolving the snapshot queries by returning data record(s) according to granularly timestamped snapshot lookup instead of singularly indexed snapshot lookup. Queries return a merged collection of records including updates from data structures in memory and in storage, such that a persistent storage transaction may refer to non-committed updates up to a timeframe defined by the snapshot read timestamp. This way, inconsistency is avoided that would result from merely reading data records committed in storage, without regard as to pending, non-committed updates thereto. The global timestamp further modifies the generation of the local transaction commit timestamp and the local snapshot read timestamp, so as to establish a granularly timestamped concurrency control scheme (over three levels of granularity).

Computer-readable media, methods, and systems are disclosed for storing and analyzing dynamic data within a semantic data store. The dynamic data comprises one or more types of data having a normalized data schema. A dynamic data manager interfaces with the semantic data store to instruct storage of the data. The data may be received through an event service from either of an external data source or an internal data source.

According to one embodiment, a data virtualization apparatus includes a memory and a processor. The processor is configured to acquire first schema information including a first table name of a first source table managed in a first data source, and second schema information including a second table name of a second source table managed in a second data source, convert the first table name into a third table name, and convert the second table name into a third table name, and register first table correspondence information including the first table name and the third table name in the memory, and register second table correspondence information including the second table name and the third table name in the memory.

Medium, method, and system for creating process automation applications. By storing applications as documents in a document database, a highly performant platform for process governance, risk management and compliance tracking is achieved. In particular, the disclosed architecture allows for rapid development of low-latency applications without requiring the application developer to write code to implement the application logic. Users can easily view a dashboard showing available applications and access them. At the same time, application developers can quickly develop new applications building on existing (previously developed or bundled) applications.

The invention discloses a processing method for process changing time-series database table structure, wherein comprising following steps: an application side generates a data table containing a table name ID, a schema version, and a column ID; when a data column is increased, the application side modifies a schema of the data table, increases the schema version, assigns a new column ID number to a newly increased column incrementally, and assigns a default value to the newly increased column; according to a data insertion request of the application side, a data node receives data of a schema version carrying a data table from the application side and writes the received data, wherein writing the received data comprises: storing the schema version of the data table carried by data from the application side by the data node, and writing the received data, and writing the received data; when the data node receives new data from the application side, comparing the schema version of the data table carried by the new data with a stored schema version of the same data table; and the data node writes data according to the comparison result. According to the method, the operation of changing the structure of a table can be completed instantly, the historical data does not need to be changed, new and old table structure definitions can be used in parallel, and the flexibility can be improved.

In a computer-implemented method for adapting time series database schema of a time series database, time series data ingested into a time series database according to a time series database schema is accessed over a time period, wherein time series data comprises a plurality of dimensions. The time series data of the time period is analyzed to determine a data shape of the time series data of the time period. It is determined whether to adapt the time series database schema based at least in part on the data shape of the time series data of the time period. In some embodiments, the time series database schema is adapted based at least in part on the data shape of the time series data of the time period. Time series data is then ingested into the time series database according to the adapted time series database schema.

Various embodiments relate generally to data science and data analysis and computer software and systems to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform configured to transmute associations between data arrangements of different formats or different data models to facilitate data operations, such as queries, configured to enhance, for example, an ingested dataset via transmuted associations as, for example, interrelations among a system of networked collaborative datasets. For example, a method may include identifying a referential indicator, determining an association with a value representative of the referential indicator to an equivalent value representative of another referential indicator associated with a different dataset, transmuting the association to form a transmuted association as a link between the value and the equivalent value, and integrating the link into an ingested data arrangement.