• Windows 11, version 22H2
• Windows 11, version 21H2
• Windows 10, version 22H2, 21H2, 20H2

<?xml version="1.0" encoding="utf-8" ?>
<configuration>
  <appSettings>
    <add key="Raven/Port" value="*"/>
    <add key="Raven/DataDir" value="~\Database\System"/>
    <add key="Raven/AnonymousAccess" value="Admin"/>
  </appSettings>
<runtime>
<loadFromRemoteSources enabled="true"/>
<assemblyBinding xmlns="urn:schemas-microsoft-com:asm.v1">
<probing privatePath="Analyzers;Plugins"/>
</assemblyBinding>
</runtime>
</configuration>

 var json = ((ServerClient) store.DatabaseCommands).CreateRequest("GET", "/debug/user-info").ReadResponseJson();

 PM> Install-Package RavenDB.Bundles.Authentication -Pre

<add key="Raven/AuthenticationMode" value="OAuth"/>

 var documentStore = new DocumentStore
{
  ApiKey = "sample/ThisIsMySecret",
  Url = "http://localhost:8080/"
};

 sys.sp_db_selective_xml_index @dbname = 'dbname', @selective_xml_index = 'action: on|off|true|false'

 for(
 pathColor = '/Item/Product/Color' as SQL nvarchar(20),
 pathSize = '/Item/Product/Size' as SQL int
)  

SELECT s.SalesOrderID,s.SalesOrderDetailID,s.OrderQty,
       LAST_VALUE(SalesOrderDetailID) OVER (PARTITION BY SalesOrderID
       ORDER BY SalesOrderDetailID)  LstValue
FROM Test_First_Last_Value s
     WHERE SalesOrderID IN (43670, 43669, 43667, 43663)
     ORDER BY s.SalesOrderID,s.SalesOrderDetailID,s.OrderQty     

SELECT s.SalesOrderID,s.SalesOrderDetailID,s.OrderQty,
       FITST_VALUE(SalesOrderDetailID) OVER (PARTITION BY SalesOrderID
       ORDER BY SalesOrderDetailID DESC) FstValue
FROM Test_First_Last_Value s
     WHERE SalesOrderID IN (43670, 43669, 43667, 43663)
     ORDER BY s.SalesOrderID,s.SalesOrderDetailID,s.OrderQty

• Linux support for tier-1, mission-critical workloads – SQL Server 2017 support for Linux includes the same high availability solutions on Linux as Windows Server, including Always On availability groups integrated with Linux native clustering solutions like Pacemaker.
• Graph data processing in SQL Server – With the graph data features available in SQL Server 2017and Azure SQL Database, customers can create nodes and edges, and discover complex and many-to-many relationships.
• Adaptive query processing – Adaptive query processing is a family of features in SQL Server 2017 that automatically keeps database queries running as efficiently as possible without requiring additional tuning from database administrators. In addition to the capability to adjust batch mode memory grants, the feature set includes batch mode adaptive joins and interleaved execution capabilities.
• Python integration for advanced analytics – Microsoft Machine Learning Services now brings you the ability to run in-database analytics using Python or R in a parallelized and scalable way. The ability to run advanced analytics in your operational store without ETL means faster time to insights for customers while easy deployment and rich extensibility make it fast to get up and running on the right model. 

 C:\>sqlcmd -S .
1> create login [MachineName\TestUser] from windows;
2> go
1> exec sp_addsrvrolemember 'MachineName\TestUser','sysadmin'
2> go
1> select is_srvrolemember('sysadmin', 'MachineName\TestUser')
2> go
-----------
1
(1 rows affected)
1>

 C:\>sqlcmd -S .
1> use master
2> go
Changed database context to 'master'.
1> create login test_user with password='123#123'
2> go
1> exec sp_addsrvrolemember 'test_user','sysadmin'
2> go
1>