SQL Server 2016 New innovations

KB Badu-AntwiSenior Program Manager, Cloud + Enterprise

Microsoft Corporation

The Microsoft data platform

Internal and

external

DashboardsReports Ask Mobile

Information

managementOrchestration

Extract, transform,

load Prediction

Relational Non-relational Analytical

Apps

Streaming

Microsoft Azure

Consistency and integration

A consistent experience from SQL Server on-premises to Microsoft Azure

IaaS and PaaS

On-premises, private cloud, and public cloud

SQL Server local, VMs, and SQL Database

Common development, management, and identity tools including Active

Directory, Visual Studio, Hyper-V, and System Center

Scalability, availability, security, identity, backup and restore, and replication

Many data sources

Reporting, integration, processing, and analytics

All supported in the hybrid cloud

Do more. Achieve more.

Performance Security Availability Scalability

Operational analyticsInsights on operational data; works with in-memory OLTP and disk-based OLTP

In-memory OLTP enhancementsGreater T-SQL surface area, terabytes of memory supported, and greater number of parallel CPUs

Query data store Monitor and optimize query plans

Native JSONExpanded support for JSON data

Temporal database supportQuery data as points in time

Always encryptedSensitive data remains encrypted at all times with ability to query

Row-level securityApply fine-grained access control to table rows

Dynamic data maskingReal-time obfuscation of data to prevent unauthorized access

Other enhancementsAudit success/failure of database operations

TDE support for storage of In-Memory OLTP tables

Enhanced auditing for OLTP with ability to track history of record changes

Enhanced AlwaysOnThree synchronous replicas for automatic failover across domains

Round-robin load balancing of replicas

Automatic failover based on database health

DTC for transactional integrity across database instances with AlwaysOn

Support for SSIS with AlwaysOn

Enhanced database caching Cache data with automatic, multiple TempDB files per instance in multicore environments

Mission-critical performance

Why temporal

• Data changes over time• Tracking and analyzing changes is often important

• Temporal in DB• Automatically tracks history of data changes

• Enables easy querying of historical data states

• Advantages over workarounds• Simplifies app development and maintenance

• Efficiently handles complex logic in DB engine

Time travel Data audit

Slowly changing dimensions

Repair record-level corruptions

Performance

Prevents data

disclosure

Client-side encryption of

sensitive data using keys that

are never given to the

database system

Queries on

encrypted data

Support for equality

comparison, including join,

group by, and distinct

operators

Application

transparency

Minimal application changes

via server and client library

enhancements

Allows customers to securely store sensitive data outside of their trust boundary.

Data remains protected from high-privileged, yet unauthorized users.

The need for Always Encrypted

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.

Benefits of row-level security (RLS)

Security

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.

Security

Benefits of dynamic data masking

Access any data Scale and manage Powerful insights Advanced analytics

PolyBaseInsights from data across SQL Server and Hadoop with the simplicity of T-SQL

Enhanced SSISDesigner support for previous SSIS versions

Enterprise-grade Analysis Services Enhanced performance and scalability for Analysis Services

Enhanced MDS Excel add-in 15x faster; more granular security roles; archival options for transaction logs; and reuse entities across models

Mobile BIBusiness insights for your on-premises data through rich visualization on mobile devices with native apps for Windows, iOS, and Android

Enhanced Reporting ServicesNew modern reports with rich visualizations

R integration Bringing predictive analytic capabilities to your relational databaseExpand your “R” script library with Microsoft Azure Marketplace

Deeper insights across data

PolyBase View in SQL Server 2016

• PolyBase View

• 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)

Access any data

SQL Server Analysis Services

Scale and manage

SQL Server 2016

Reporting Services

(Native mode)

Datazen Server now a

component of SSRS

CREATE

SQL Server 2016Reporting Services

(SharePoint integrated mode)

Datazen Windows app

Datazen Android app

Datazen iOS app

Report Server web portal(paginated and mobile reports)

Datazen Publisher

SQL Server Report Builder

Report Designer inSQL Server Data Tools

Datazen phone app

Pin paginated report elements

to Power BI dashboards

SSRS reports rendered as PDF

SharePoint web

SQL Server 2016 Reporting Services and mobile reporting

MANAGE CONSUME

Powerful insights

Capability

Extensible in-database analytics, integrated with R,

exposed through T-SQL

Centralize enterprise library for analytic models

Benefits

SQL Server

Analytical engines

Full R integration

Fully extensible

Data Management Layer

Relational data

T-SQL interface

Stream data in-memory

Analytics library

Share and collaborate

Manage and deploy

R +

Data Scientists

Business Analysts

Publish algorithms, interact

directly with data

Analysis through TSQL, tools,

and vetted algorithms

DBAsManage storage and analytics

together

Advanced analytics

R integration and Advanced Analytics

Hybrid solutions Simplicity Consistency

Stretch DatabaseStretch operational tables in a secure manner into Azure for cost-effective historic data availability.Works with Always Encrypted and row-level security

Power BI with on-premises dataNew interactive query with Analysis Services. Customer data stays behind your firewall

Enhanced backup to AzureFaster restore times and 50% reduction in storage. Supports larger DBs with block blobs and custom backup schedule with local staging

Easy migration of on-premises SQL ServerSimple point-and-click migration to Azure

Suite of advisors for upgrading to SQL Server 2016SQL Server 2016 Upgrade Advisor in the adoption of new SQL Server features

Simplified Add Azure Replica Wizard Automatic listener configuration for AlwaysOn in Azure VMs

Common development, management, and identity toolsIncluding Active Directory, Visual Studio, Hyper-V, and System Center

Consistent experience from SQL Server on-premises to Microsoft Azure IaaS and PaaS

Hyperscale Cloud

Order historyName SSN Date

Jane Doe cm61ba906fd2/28/200

5

Jim Gray ox7ff654ae6d3/18/200

5

John Smith i2y36cg776rg4/10/200

5

Bill Brown nx290pldo90l4/27/200

5

Sue Daniels ypo85ba616rj5/12/200

5

Sarah Jones bns51ra806fd5/22/200

5

Order history

Name SSN Date

Jane Doe cm61ba906fd 2/28/2005

Jim Gray ox7ff654ae6d 3/18/2005

John Smith i2y36cg776rg 4/10/2005

Bill Brown nx290pldo90l 4/27/2005

Customer data

Product data

Order History

Stretch to cloud

Hybrid solutions

App

Query

Microsoft Azure

Jim Gray ox7ff654ae6d 3/18/2005

Summary: stretch SQL Server into Azure

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The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on

the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.