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SQL Server 2016 : New  Features

Andriy Zrobok EPAM Lviv

August 4, 2015

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SQL Server 2016 Community Technology Preview 2

Now Available: SQL Server 2016 Community Technology Preview 2

"It is the biggest leap forward in Microsoft's data platform history with real-time operational analytics, rich visualizations on mobile devices, built-in advanced analytics, new advanced security technology, and new hybrid cloud scenarios."

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Agenda

• Data security: Always Encrypted / Row Level Security / Dynamic Data Masking• Hybrid Cloud Solution: Stretch Database / Hybrid backups

• Performance: Real-time Operational Analytics & In-Memory OLTP / Query Store / Native JSON support

• BI: Built-in Advanced Analytics (R integration)/ PolyBase / Mobile BI• BI by products:

• Cloud - Power BI - for Office365 customers only right now (expose on-premises multidimensional cubes and tabular models in cloud )

• Analysis Services Tabular: Many-to-many relationships / New DAX functions / etc.• Analysis Services Dimensional: Netezza as a Data Source / Unnatural hierarchies / Distinct counts / etc.

• T-SQL: System-Versioned Temporal Tables• TempDB (amounts of files), Etc.

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Always Encrypted – a new capability that

protects data at rest and in motion.

However, if the data is encrypted before it hits the database, you need to consider the following scenarios:

• Analytics queries – your analytics and reporting apps will have to be equipped to decrypt the data if you need to show it onscreen

• Range queries – if you need to see all of the users whose last names are like Smi%, you need to decrypt them

• Replication – if you want to copy the data from one SQL Server to another, it usually needs to be decrypted on the way out

Always Encrypted

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Row-Level Security (RLS) restricts which users can view what data in a table, based on a function. SQL Server 2016 introduces this feature, which is very useful in multi-tenant environments where you may want to limit data access based on customer ID

Row Level Security

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Dynamic Data Masking

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Dynamic Data Masking

The Default mask returns 'XXXX', 0, or '01.01.2000 …' depending on the data type.1

The Email mask returns 'aXX@XXXX.com' where “a” is the first letter in the email address and “com” is the top-level domain name.

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The Partial mask return the first N characters, a constant expression such as 'XXX-XX-XX' and the last M characters.

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Dynamic Data Masking: Real-time obfuscation of data to prevent unauthorized access

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Stretch Database – new technology that

lets you dynamically stretch your warm and

cold transactional data to Microsoft Azure

Enhanced hybrid backup to Azure -- Enables faster backups to Microsoft Azure and faster restores to SQL Server in Azure Virtual Machines. Also, you can stage backups on-premises prior to uploading to Azure.

Stretch Database

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Real-time Operational Analytics & In-Memory OLTP

Microsoft introduces the unique capability to use our in-memory column store delivering 100X faster queries with in-memory OLTP for in-memory performance and real-time operational analytics.

Limitations:• Like other indexes on a Memory Optimized Table, the Columnstore Index must be defined when the table is created.• The Columnstore Index must include all columns in the base table. (This limitation doesn’t exist for Columnstore Indexes on normal tables.)• The Columnstore Index must include all rows in the base table. Or in other words, it can’t be a filtered index.

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In-Memory OLTP (2014 vs 2016) Promise

https://myignite.microsoft.com/#/videos/bc3b10f5-13b4-e411-b87f-00155d5066d7

Kevin Farlee Senior Program Manager, MicrosoftSunil Agarwal Principal Program Manager, Microsoft

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In-Memory OLTP (2014 vs 2016) CTP testing

Feature/Limit MS SQL 2014 MS SQL 2016

Maximum size of durable table 256 MB 2TB ?

LOB (varbinary(max), [n]varchar(max)) Not supported Supported (not in CTP) ?

Transparent Data Encryption (TDE) Not supported Supported ?

ALTER PROCEDURE / sp_recompile Not supported Supported (fully online)

Nested native procedure calls Not supported Supported

Natively-compiled scalar UDFs Not supported Supported (no clear documentation in MSDN)?

ALTER TABLE Not supported Partially supported (offline)

DML triggers Not supported Not Supported (MSDN)

Indexes on NULL-able columns Not supported Not Supported

Foreign Keys \Check/Unique Constraints Not supported Not Supported

Parallelism Not supported Supported ?

OUTER JOIN, OR, NOT, UNION [ALL], DISTINCT, EXISTS, IN Not supported Supported (Natively-compiled sp)

SSMS Table Designer Not supported Supported

http://sqlperformance.com/2015/05/sql-server-2016/in-memory-oltp-enhancementshttps://msdn.microsoft.com/en-us/library/dn246937.aspx

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In-Memory OLTP (2014 vs 2016) MSDN

https://msdn.microsoft.com/en-us/library/dn246937.aspx

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Query Store

Query Data Store: Monitor and optimize query plans with full history of query execution

One common problem many organizations face when upgrading versions of SQL Server is changes in the query optimizer (which happen from version to version) negatively impacting performance. Without comprehensive testing, this has traditionally been a hard problem to identify and then resolve. The Query Store feature maintains a history of query execution plans with their performance data, and quickly identifies queries that have gotten slower recently, allowing administrators or developers to force the use of an older, better plan if needed. The Query Store is configured at the individual database level.

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Native JSON

JSON (JavaScript Object Notation) is a standardized data exchange format that is currently not supported natively by SQL Server. To perform JSON imports and exports you need to hand-code complex T-SQL, SQLCLR or JavaScript. SQL Server 2016 promises to simply this by incorporating JSON support directly into SQL Server much like XML. SQL Server 2016 will natively parse and store JSON as relational data and will support exporting relational data to JSON.

While this has also been hotly requested, I’d caution you to be careful what you ask for. Users demanded XML support inside SQL Server, and then proceeded to use SQL Server as an XML query engine, sending CPU through the roof. SQL Server is one of the world’s most expensive application servers.http://www.brentozar.com/archive/2015/05/reading-the-sql-server-2016-data-sheet/

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Built-in Advanced Analytics

As a specialized, open source statistical environment, R represents the primary analysis language for the majority of data scientists and statisticians. In recent years, R has also undergone a significant shift in user base by gaining wider adoption in the business world. By marrying R with its core data platform, Microsoft is signaling that it is serious about advancing its analytic offerings not only in the cloud, but on - premise as well. This vision will help accelerate the current trend and lead the R language into mainstream use.

Just like you can run your C# code in the database, too. Or your XML parsing. Or your JSON. If you wanna do your processing in a $7k USD per core database server, Microsoft wants to empower you to do it. I would too, if I was wearing their exceedingly good-looking and expensive shoes. I like the way they think.http://www.brentozar.com/archive/2015/05/reading-the-sql-server-2016-data-sheet

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PolyBase

In a nutshell, PolyBase is a technology in SQL Server 2012 PDW that allows you to query both data from both within your SQL Server PDW and Hadoop environments at the same time.

SQL Server 2016: Microsoft has incorporated that functionality into the regular on-premises product. This feature will benefit you if your regular data processing involves dealing with a lot of large text files -- they can be stored in Azure Blob Storage or Hadoop, and queried as if they were database tables

Use case: ETL process, text file processing

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Mobile BI

Business insights for your on-premises data through rich visualizations on mobile devices with native apps for Windows, iOS and Android

Microsoft recently acquired DataZen, a reporting tool that focuses on mobile devices, and promptly gave it away free to most Enterprise Edition customers. The simplest way to accomplish this feature would be to simply throw DataZen’s existing code in free with the SQL Server boxed product.

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1. Demo 1: JSON

2. Demo 2: data masking

3. Demo 3: row level security

4. Demo 4: temporal tables

5. Demo 5: in-memory OLTP (Promise and Reality)

Demos

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MS SQL 2016 – New Features

Q&AThe End