Salesforce Com, Inc.

Salesforce, Inc.

Eli Levine

Jonathan Bruce

Simon Toens

Samarpan Jain

Jan Asita Fernando

Ian Varley

James Ferguson

James G Taylor

Cody Marcel

Ming-Yang Chen

Saikiran Perumala

Karl Ryszard Skucha

Ka Chun Au

Alex S Warshavsky

Adam Torman

Pawan Nachnani

Susan S Levine

Brian Esserlieu

Kit Pang Szeto

Johnson Liu

Christopher James Wu

Shu Liu

Eric Shahkarami

Yuk Hei Chan

Bilong Chen

Dan Milbrath

Bharadwaj Tanikella

Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.

Techniques for data retention

Systems, methods, and computer-readable media for asynchronous (async) querying are described. In embodiments, an application server obtains a user-issued query comprising one or more query components; identifies data space characteristics of a data storage space associated with a user that issued the user-issued query; and analyzes the one or more query components to obtain performance data. The performance data is indicative of resource consumption for execution of the user-issued query. The application server selects a query execution engine to execute the user-issued query from among a plurality of query execution engines, and provides the user-issued query to the selected query execution engine. The selection is based on the data space characteristics and the performance data. Other embodiments may be described and/or claimed.

Technologies for runtime selection of query execution engines

Disclosed are examples of systems, apparatus, methods and computer program products for providing run-time querying of multi-tenant non-relational database objects. A database system maintains a multi-tenant non-relational database associated with a number of enterprises, a number of records, and a number of data objects for each of the enterprises, each data object having at least one composite key field. A request is received during runtime to query data related to a data object, and the system determines that the data object is defined to be used in associated with a non-relational database. The system then retrieves a metadata model of the data object, determines that the request includes at least one composite key field for the data object, and processes the requery to query data in synchronous fashion. Finally, a query response is provided to the user.

Run-time querying of multi-tenant non-relational platform objects

Systems, methods, and computer-readable media for asynchronous (async) querying are described. In embodiments, a system may convert a user-issued query into a distributed execution instruction set (DEIS), and issue the DEIS to data stores that may have various database structures. The system may obtain database objects from the data stores, and store a result set indicating the obtained database objects in a location specified by the user-issued query. The system may also provide mechanisms to allow users to view progress of their async query jobs and/or cancel ongoing async query jobs. Other embodiments may be described and/or claimed.

Technologies for asynchronous querying

Techniques and systems for completing a database query. A time to complete a synchronous query in response to receiving an original database query is estimated by a database management system provided by one or more computing devices. A synchronous database query corresponding to the original database query is performed with the database management system if the estimated time to complete the synchronous query is less than a pre-selected threshold time. One or more asynchronous queries corresponding to the original database query are performed with the database management system if the estimated time to complete the synchronous query is greater than the pre-selected threshold time. A result, whether from a synchronous query or one or more asynchronous queries, is stored in an object within a non-relational database system.

Asynchronous search for big objects

Techniques and structures for providing a multitenant environment having both a relational database and a non-relational database. A database query is received with at least one server computing device providing a multitenant environment having a relational database system and a non-relational database system, the database query in a format corresponding to the relational database system. The query is parsed with the at least one server computing device to find one or more components of the query directed to data stored in the non-relational database system. One or more components of the query directed to data stored in the non-relational database system are converted to one or more scans of the non-relational database system. Results from the query of the relational database system and results from the one or more scans of the non-relational database system are collected. The results from the query and the results of the one or more scans to a combined result are combined. The combined results are provided to a client entity.

Multi-tenancy for structured query language (SQL) and non structured query language (NOSQL) databases

Methods, systems, and devices for data retention handling are described. In some data storage systems, data objects are stored in a non-relational database schema. The system may support configurable data retention policies for different tenants, users, or applications. For example, a data store may receive retention requests, where the retention requests may specify deletion or exportation actions to perform on records contained within data objects. The data store may determine retention rules based on these retention requests, and may periodically or aperiodically evaluate the rules to determine active actions to perform. To improve the efficiency of the system, the data store may aggregate the active actions (e.g., according to the dataset to perform the actions on), and may generate work items corresponding to the aggregate actions. A work processor may retrieve these work items and may efficiently perform the data retention actions on datasets stored in the data object store.

Data retention handling for data object stores

Methods, systems, and devices for data access and processing are described. To set up secure environments for data processing (e.g., including machine learning), an access control system may first receive approval from an authorized user (e.g., an approver) granting access to data objects in a multi-tenant data store. The system may determine tenant-specific paths for retrieving the data objects from the data store, and may initialize a number of virtual computing engines for accessing the data. Each computing engine may be tenant-specific based on the path(s) used by that computing engine, and each may include an access role defining the data objects or data object types accessible by that computing engine. By accessing the requested data objects according to the tenant-specific path prefixes and access roles, the virtual computing engines may securely maintain separate environments for different tenants and may only allow user access to approved tenant data.

Securely accessing and processing data in a multi-tenant data store

Multi-tenancy for structured query language (SQL) and non structured query language (NoSQL) databases

Disclosed are examples of systems, apparatus, methods and computer program products for providing application programming interface representation for multi-tenant non-relational database objects. A database system maintains a multi-tenant non-relational database associated with a number of enterprises, a number of records, and a number of data objects for each of the enterprises. A request is received from a user to retrieve a description of a data object from the number of data objects, and in response, the system determines that the data object is defined to be used in associated with a non-relational database, then retrieves a metadata model representing the data object. The system determines that at least one field of the data object is part of a composite key for the data object, then provides data object information to the user, including information about the composite key.

Application programming interface representation of multi-tenant non-relational platform objects

Disclosed are examples of systems, apparatus, methods and computer program products for providing a web application builder framework in a database system. A database system maintains a multi-tenant non-relational database associated with a number of enterprises, a number of records, and a number of data objects for each of the enterprises. A dynamic virtual table is maintained as well, associated with the number of records and number of data objects. A user request is received to define a composite key for a data object. A metadata model is generated representing the data object, and a data definition script is generated. The dynamic virtual table is updated to include one or more virtual columns corresponding to the data definition script, and one or more columns of a shared table in the non-relational database are updated to match the virtual columns.

Composite keys for multi-tenant non-relational platform objects

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San Francisco, CA, United States of America

Eli Levine