The document outlines the new features and business benefits of SQL Server 2016, highlighting its capabilities in operational database management, business intelligence, and data warehousing as recognized by Gartner. It details the various editions of SQL Server 2016, their features related to security, analytics, and hybrid solutions, as well as improvements in data management, availability, and integration with cloud services. Key enhancements include advanced security features, in-memory processing, real-time analytics, and improved manageability to provide enterprise-level solutions.

1. SQL Server 2016
New Features &
Business Benefits
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Nottingham
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2. Microsoft is a market leader for…..
[1] *Gartner “Magic Quadrant for Operational Database Management Systems,” by Donald Feinberg , Merv Adrian , Nick Heudecker, Adam Ronthal, October 2015
[2] *Gartner “Magic Quadrant for Business Intelligenceand Analytics Platforms,” by Rita Sallam and Josh Parenteau, February 23, 2015
[3] *Gartner “Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics,” by Mark Beyer and Roxane Edjlali, February 12, 2015
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is availableupon request from Microsoft. Gartner does not endorse any vendor, product or service depicted in its research publications, and does
not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publicationsconsist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties,expressed or implied, with respect to this
research, includingany warranties of merchantability or fitness for a particular purpose.
Magic Quadrant for Data Warehouse
Database Management Solutions3
A leader for the fourth consecutive year
Magic Quadrant for Business Intelligence
and Analytics Platforms2
A leader 8 years running
Magic Quadrant for Operational
Database Management Systems1
Furthest in vision and ability to execute

3. SQL Server 2016: Everything built-in
The above graphics were published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Microsoft. Gartner does not endorse any vendor, product or service depicted in its
research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all
warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Consistent experience from on-premises to cloud
Microsoft Tableau Oracle
$120
$480
$2,230
Self-service BI per user
In-memoryacrossall workloads
TPC-H non-clustered results as of 04/06/15, 5/04/15, 4/15/14 and 11/25/13, respectively. http://www.tpc.org/tpch/results/tpch_perf_results.asp?resulttype=noncluster
at massive scale
0 1
4
0 0
3
34
29
22
15
5
22
6
43
20
69
18
49
3
0
10
20
30
40
50
60
70
80
2010 2011 2012 2013 2014 2015
SQL Server Oracle MySQL SAP HANA TPC-H non-clustered 10TB
Oracle
is #5#2
SQL Server
#1
SQL Server
#3
SQL Server
National Institute of Standards and Technology Comprehensive Vulnerability Database update 10/2015

4. SQL 2016 Editions – what’s New
EnterpriseStandardExp.

5. SQL Server 2016 Features by Edition (General)
Feature Express Standard Enterprise
Maximum number of cores 4 cores 24 cores Unlimited
Maximum memory utilized per instance 1 GB 128 GB OS Max
Maximum size 10 GB 524 PB 524 PB
Production use rights   
Basic OLTP   
Manageability (Management Studio, Policy-Based Management)   
Basic high availability (2-node single database failover,
non-readable secondary)   
Enterprise data management (Master Data Services, Data Quality
Services)   
Advanced OLTP (In-memory OLTP, Operational analytics)   
Advanced HA (Always On - multi-node, multi-db failover, readable
secondary's)   

6. SQL Server 2016 Features by Edition
(Security, DW, Analytics & Hybrid)
Feature Express Standard Enterprise
Basic security (Row-level security, data masking, basic auditing,
separation of duties)   
Advanced security
(Transparent Data Encryption, Always Encrypted)   
Advanced data integration (Fuzzy grouping and look ups, change data
capture)   
Data warehousing (In-Memory ColumnStore, Partitioning)   
Basic “R” integration (Connectivity to R Open, Limited parallelism
for RRE)   
Advanced “R” integration (Full parallelism for RRE)   
Stretch Database   

7. SQL Server 2016 Features by Edition (Business
Intelligence)
Feature Express Standard Enterprise
Programmability & developer tools (T-SQL, CLR, Data Types,
FileTable, JSON)   
Basic reporting & analytics   
Basic data integration (SSIS, built-in connectors)   
Basic Corporate Business Intelligence (Multi-dimensional models,
Basic tabular model)   
Mobile BI (Datazen)   
Advanced Corporate Business Intelligence (Advanced tabular
model, Direct query, in-memory analytics, advanced data mining)   

8. Stretch SQL Server into Azure (Stretch Database)
Capability
 Stretch large operational tables
from on-premises to Azure with
the ability to query
Benefits
SQL
SERVER
2016
Azure
Hybrid solutions
Customer data
Product data
Order History
Stretch to cloud

9. JSON in SQL Server 2016
[
{
"Number":"SO43659",
"Date":"2011-05-31T00:00:00"
"AccountNumber":"AW29825",
"Price":59.99,
"Quantity":1
},
{
"Number":"SO43661",
"Date":"2011-06-01T00:00:00“
"AccountNumber":"AW73565“,
"Price":24.99,
"Quantity":3
}
]
Number Date Customer Price Quantity
SO43659 2011-05-31T00:00:00 MSFT 59.99 1
SO43661 2011-06-01T00:00:00 Nokia 24.99 3
Table 2 JSON
Formats result set
as JSON text.
JSON 2 table
Migrates JSON
text to table
Built-in functions
ISJSON
JSON_VALUE
JSON_MODIFY
Performance
Note: No custom type or index, stored as NVARCHAR

10. Always Encrypted: How it works
Help protect data at rest and in motion, on-premises and in
the cloud
SQL Server or SQL Database
ADO .NET
Name
Wayne Jefferson
Name
0x19ca706fbd9a
Result SetResult Set
Client
Name SSN Country
0x19ca706fbd9a 0x7ff654ae6d USA
dbo.Customers
ciphertext
"SELECT Name FROM Customers WHERE SSN = @SSN",
0x7ff654ae6d
ciphertext
"SELECT Name FROM Customers WHERE SSN =
@SSN",
"111-22-3333"
Encrypted sensitive data and corresponding keys
are never seen in plaintext in SQL Server
trust boundary
Security

11. Always Encrypted
Help protect data at rest and in motion, on-premises and in
the cloud
Data remains encrypted
during query
Capability
ADO.Net client library provides
transparent client-side encryption,
while SQL Server executes T-SQL
queries on encrypted data
Benefits
Apps TCE-enabled
ADO .NET library
SQL ServerEncrypted
query
Columnar
key
No app
changes
Master
key
Security

12. Row Level Security
Fine-grained access control over specific rows in a database
table
Help prevent unauthorized access when multiple users share the
same tables, or to implement connection filtering in multitenant
applications
Administer via SQL Server Management Studio or SQL Server
Data Tools
Enforcement logic inside the database and schema is bound to
the table
Protect data privacy by ensuring
the right access across rows
SQL Database
Customer 1
Customer 2
Customer 3
Security

13. Row Level Security
Fine-grained access
control
Keeping multitenant databases
secure by limiting access by
other users who share the same
tables
Application
transparency
RLS works transparently at
query time, no app changes
needed
Compatible with RLS in other
leading products
Centralized security
logic
Enforcement logic resides
inside database and is schema-
bound to the table it protects
providing greater security.
Reduced application
maintenance and complexity
Store data intended for many consumers in a single database/table while at the same time
restricting row-level read and write access based on users’ execution context.

14. Data Masking
Configuration made easy in the new Azure portal
Policy-driven at the table and column level, for a
defined set of users
Data masking applied in real-time to query results
based on policy
Multiple masking functions available (e.g. full,
partial) for various sensitive data categories (credit
card numbers, SSN, etc.)
SQL Database
SQL Server 2016
Table.CreditCardNo
4465-6571-7868-5796
4468-7746-3848-1978
4484-5434-6858-6550
Real-time data masking;
partial masking
Prevent the abuse of sensitive
data by hiding it from users
Security

15. Data Masking
Regulatory
compliance
Sensitive data
protection
Agility and
transparency
Data is masked on the fly, with
underlying data in the database
remaining intact. Transparent to
the application and applied
according to user privilege
Limit access to sensitive data by defining policies to obfuscate specific database fields,
without affecting the integrity of the database.

16. Enhanced AlwaysOn Availability Groups
Greater scalability
 Load balancing readable secondaries
 Increased number of automatic
failover targets
 Log transport performance
Improved manageability
 DTC support
 Database-level health monitoring
 Group Managed Service Account
 Domain-independent Availability
Groups
AG_Listener
New York
(Primary)
Asynchronous data
Movement
Synchronous data
Movement
Unified HA solution
AG
Hong Kong
(Secondary)
AG
New Jersey
(Secondary)
AG

17. Enhanced AlwaysOn Availability Groups
Load balancing in readable secondary's
Computer5
DR site Computer2
Computer3
Computer4
Primary
site
Computer1
(Primary)
READ_ONLY_ROUTING_LIST=
(('COMPUTER2', 'COMPUTER3',
'COMPUTER4'), 'COMPUTER5')
 In SQL 2014, read-only
transactions routed by the
Listener went to the first
secondary that was available
 Read-only Routing (ROR) lists
 Now you can configure the
ROR lists to round-robin
among a specific set of
secondary's (for each
primary)
Availability

18. Polybase view in SQL Server 2016
 Execute T-SQL queries against
relational data in SQL Server and
‘semi-structured’ data in HDFS
and/or Azure
 Leverage existing T-SQL skills and BI
tools to gain insights from different
data stores
 Expand the reach of SQL Server to
Hadoop(HDFS)

19. Revolution R Enterprise & SQL
Big data analytics platform
Based on open source R
High-performance, scalable, full-featured
Statistical and machine-learning algorithms are
performant, scalable, and distributable
Write once, deploy anywhere
Scripts and models can be executed on a variety of
platforms, including non-Microsoft (Hadoop,
Teradata in-DB)
Integration with the R Ecosystem
Analytic algorithms accessed via R function with similar
syntax for R users. Arbitrary R functions/packages can
be used in conjunction

20. Real-time operational analytics – In Memory
0100101010110
In-memory
ColumnStore
In-memory
OLTP
Real-time business problem
detection
 Up to 30x faster
transactions with
in-memory OLTP
 Queries from
minutes to
seconds
 Real-time
operational
analytics

21. Mobile BI for SQL Server
Business insights through rich visualizations
on any device
Native apps for Windows,
iOS and Android
 Create once and publish to any device
 Access your data from anywhere
 Custom branding
 Touch-optimized data exploration and perfect
scaling to any screen form-factor
 Collaborate with colleagues on the go

22. Customer References

23. Thank you