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clarifying note on RLS

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Jos de Bruijn
2016-06-03 09:27:48 -07:00
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samples/databases/wide-world-importers/documentation/wwi-oltp-htap-sql-features.md
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@ -7,7 +7,7 @@ WideWorldImporters is designed to showcase many of the key features of SQL Serve
|Temporal tables|There are many temporal tables, including all look-up style reference tables and main entities such as StockItems, Customers, and Suppliers. Using temporal tables allows to conveniently keep track of the history of these entities.|
|AJAX calls for JSON|The application frequently uses AJAX calls to query these tables: Persons, Customers, Suppliers, and StockItems. The calls return JSON payloads (i.e. the data that is returned is formatted as JSON data). See, for example, the stored procedure `Website.SearchForCustomers`.|
|JSON property/value bags|A number of tables have columns that hold JSON data to extend the relational data in the table. For example, `Application.SystemParameters` has a column for application settings and `Application.People` has a column to record user preferences. These tables use an `nvarchar(max)` column to record the JSON data, along with a CHECK constraint using the built-in function `ISJSON` to ensure the column values are valid JSON.|
|Row-level security (RLS)|Row Level Security (RLS) is used to limit access to the Customers table, based on role membership. Each sales territory has a role and a user. To see this in action, a script to demonstrate it has been provided.|
|Row-level security (RLS)|Row Level Security (RLS) is used to limit access to the Customers table, based on role membership. Each sales territory has a role and a user. To see this in action, use the corresponding script in sample-script.zip, which is part of the [release of the sample](http://go.microsoft.com/fwlink/?LinkID=800630).|
|Real-time Operational Analytics|(Full version of the database) The core transactional tables `Sales.InvoiceLines` and `Sales.OrderLines` both have a non-clustered columnstore index to support efficient execution of analytical queries in the transactional database with minimal impact on the operational workload. Running transactions and analytics in the same database is also referred to as [Hybrid Transactional/Analytical Processing (HTAP)](https://wikipedia.org/wiki/Hybrid_Transactional/Analytical_Processing_(HTAP)).|
|In-Memory OLTP|(Full version of the database) The table types are all memory-optimized, such that table-valued parameters (TVPs) all benefit from memory-optimization.<br/><br/>The two monitoring tables, `Warehouse.VehicleTemperatures` and `Warehouse.ColdRoomTemperatures`, are memory-optimized. This allows the ColdRoomTemperatures table to be populated at higher speed than a traditional disk-based table. The VehicleTemperatures table holds the JSON payload and lends itself to extension towards IoT scenarios. The VehicleTemperatures table further lends itself to scenarios involving EventHubs, Stream Analytics, and Power BI.<br/><br/>The stored procedure `Website.RecordColdRoomTemperatures` is natively compiled to further improve the performance of recording cold room temperatures.|
|Clustered columnstore index|(Full version of the database) The table `Warehouse.StockItemTransactions` uses a clustered columnstore index. The number of rows in this table is expected to grow large, and the clustered columnstore index significantly reduces the on-disk size of the table, and improves query performance. The modification on this table are insert-only - there is no update/delete on this table in the online workload - and clustered columnstore index performs well for insert workloads.|