<> Full encryption technology (Always Encrypted)

Full encryption technology (Always Encrypted) Support in SQL Server Keep data encryption in , Only call SQL Server
To access encrypted data . This function supports client application owner to control confidential data , Specify who has access .SQL Server 2016
By verifying the encryption key, the client application is controlled . The encryption key is never passed to SQL Server
. Use this function , You can avoid database or operating system administrators from accessing client application sensitive data ( Including static data and dynamic data ). This feature now supports the storage of sensitive data in the cloud management database , And always keep it encrypted . Even cloud providers don't see data , You can have a good night's sleep .

<> Dynamic data masking (Dynamic Data Masking)

If you're interested in protecting data , I hope some people can see the encrypted data , Others can only see the scrambled code after the encrypted data is confused , So you'll be interested in dynamic data masking . Using dynamic data masking function , You can
SQL Server
Column confusion of data to be encrypted in database table , Those unauthorized users can't see this data . Using dynamic data masking function , You can also define how data is obfuscated . for example , If you receive a stored credit card number in the form , But you want to see only the last four . Using the dynamic data masking function to define the screening rules can limit the unauthorized users to see only the last four digits of the credit card number , Users with permission can see the complete credit card information .

<>JSON support

JSON namely JavaScript Object Notation( Lightweight data exchange format ). stay SQL Server 2016 in , You can now apply and SQL
Server Between database engines JSON Format interaction . Microsoft in SQL Server Added a pair of JSON Support for , Can be resolved JSON Format data is then stored in a relational format . in addition , Using the right
JSON Support for , You can also convert relational data into JSON Format data . Microsoft has also added a number of functions to provide access to the SQL Server Medium JSON Data execution query .SQL Server
With these built-in enhanced support JSON Function of operation , Application usage JSON Data and SQL Server It's easier to interact .

<> many TempDB Database file

If you're running a multicore computer , Then run multiple tempdb Data files are best practices . Before until SQL Server 2014 edition , You install SQL Server
After that, you always have to add it manually tempdb data file . stay SQL Server 2016 in , You can now install the SQL Server You need to configure them directly tempdb
Number of documents . So you don't need to add it manually after installation tempdb It's a document .

<>PolyBase

PolyBase Support query of distributed data sets . Yes PolyBase, You can use it Transact SQL Statement query Hadoop perhaps SQL Azure blob
storage . You can use it now PolyBase Write temporary query , realization SQL Server Relational data and Hadoop perhaps SQL Azure blog
Association query between semi structured data in storage . in addition , You can also use it SQL Server Dynamic column storage index for semi-structured data to optimize query . If an organization passes data across multiple distributed locations ,
PolyBase It's a use SQL Server Technology provides a convenient solution for accessing semi-structured data in these locations .

<>Query Store

If you use execution plans often , You'll love the new version Query Store function . stay 2016 In previous versions , You can use dynamic management to try (DMV) To view the existing execution plan . however ,DMV
It only supports you to view the currently active plans in the plan cache . If there is a plan cache , You don't see the history of the plan . Yes Query Store function ,SQL
You can now save the history execution plan . More Than This , This function can also save the query statistics of those historical plans . This is a good complement , You can use this feature to track the performance of execution plans over time .

<> Bank level security (Row Level Security)

SQL After the database engine has row level security features , According to the SQL Server
Login permissions restrict access to row data . Restricting rows is implemented by filtering predicate definitions with inline table valued functions . The security policy ensures that the filter predicate gets every time “SELECT” perhaps “DELETE
” Operation execution . Implementing row level security at the database level means that application developers no longer need to maintain code to restrict certain logins or allow certain logins to access all data . With this feature , When a user queries a table that contains row level security settings , They don't even know that the data they are querying is part of the data that has been filtered .

<>SQL SERVER support R language

Microsoft acquisition Revolution Analytics After the company , Now you can SQL Server On the use of big data R Language to do advanced analysis function .SQL Server support R
After language processing , Data scientists can use existing data directly R Code and in SQL Server Running on the database engine . So we don't have to do it for execution R Language is used to process data SQL Server
Data export processing . This function will R Language processing brings data .

( Translation notes :Revolution Analytics The company is a spin off of Yale University , Established in 2007 year , Is an open source based project R
Language as a supplier of computer software and services . The company was acquired by Microsoft last year .)

<>Stretch Database

Stretch Database Function provides the ability to extend the on premises database to Azure SQL The way of database . Yes Stretch Database
function , The most frequently accessed data is stored in the internal database , Data with less access will be stored offline in the Azure SQL In the database . When you set the database to “stretch
“ Time , The older data will be migrated to the Azure SQL database . If you need to run queries to access active data and stretched
Historical information in database , The database engine will combine the internal database and Azure SQL Seamless database docking , The query will return the result you want , It's like being in the same data source . This function enables DBA
It's easier to work , They can archive historical information and move to cheaper storage media , There is no need to modify the current actual application code . In this way, you can keep the common internal database queries in the best performance .

<> History table (Temporal Table)

The history table saves the old version information of the data in the base table . With the history table function ,SQL Server
It will automatically manage and migrate the old data version to the history table every time there is a row update in the base table . The history table is physically another table independent of the base table , But it is related to the base table . If you have built or plan to build your own methods to manage the row data version , So you should have a look first
SQL Server 2016 History table function provided by China Singapore , Then decide whether you need to build your own solution .

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