1. SQL Server 2016 : New Features
Andriy Zrobok EPAM Lviv
August 4, 2015

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."

3. 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.

4. Always Encrypted 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

5. Row Level Security
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

6. Dynamic Data Masking

7. Dynamic Data Masking
Dynamic Data Masking: Real-time obfuscation of data to prevent unauthorized access
The Default mask returns 'XXXX', 0, or ' …' depending on the data type. 1
The mask returns where “a” is the first letter in the address and “com” is the top-level domain name. 2
The Partial mask return the first N characters, a constant expression such as 'XXX-XX-XX' and the last M characters. 3

8. Stretch Database
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.

9. 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.

10. In-Memory OLTP (2014 vs 2016) Promise
Kevin Farlee Senior Program Manager, Microsoft
Sunil Agarwal Principal Program Manager, Microsoft

11. 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)
Supported ?
ALTER PROCEDURE / sp_recompile
Supported (fully online)
Nested native procedure calls
Supported
Natively-compiled scalar UDFs
Supported (no clear documentation in MSDN)?
ALTER TABLE
Partially supported (offline)
DML triggers
Not Supported (MSDN)
Indexes on NULL-able columns
Not Supported
Foreign Keys \Check/Unique Constraints
Parallelism
Supported ?
OUTER JOIN, OR, NOT, UNION [ALL], DISTINCT, EXISTS, IN
Supported (Natively-compiled sp)
SSMS Table Designer

12. In-Memory OLTP (2014 vs 2016) MSDN

13. 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.

14. 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.

15. 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.

16. 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

17. 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.

18. Demos Demo 1: JSON Demo 2: data masking Demo 3: row level security
Demo 4: temporal tables
Demo 5: in-memory OLTP (Promise and Reality)

19. MS SQL 2016 – New Features
Q&A
The End