1. Microsoft Ignite 2015 4/16/2017 3:29 PM
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

2. SQL Server Evolution SQL 2016 new innovations – Part 2 Lindsey Allen
Principal Group Program Manager
Borko Novakovic
Program Manager

3. What’s in this session SQL 2016 highlights
Scaling up to new heights – 16 sockets
In-memory Engine Advances
Query flight recorder - Query Store
Time travel and auditing with Temporal database
Bring Advanced Analytics to your data
Call to action

4. Mission critical platform
Performance
Security
Availability
Scalability
Operational analytics
Minimize performance impact running real-time analytics on transaction data
Avoid data sprawl
In-memory OLTP for more applications
Query Store
Always Encrypted
Row level security
Dynamic Data Masking
Enhanced AlwaysOn
3 synchronous replicas for auto failover across domains
Round robin load balancing of replicas
DTC for transactional integrity across database instances with AlwaysOn
Enhanced online operations
Support for Windows Server 2016
12TB 16 Sockets

5. Demo
SQL scalability on HP superdomeX
Lindsey Allen

6. In-memory engine Faster Transactions Faster Queries IN-MEMORY OLTP
4/16/2017
In-memory engine
Faster Transactions
IN-MEMORY OLTP
Faster Queries
IN-MEMORY DW
Up to 30x faster transaction processing with In-Memory OLTP
Over 100x query speed and significant data compression with
In-Memory ColumnStore
© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
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.

7. In-memory OLTP Hardware trends Business
Customer Benefits
High performance data operations
Efficient business-logic processing
Frictionless scale-up
Hybrid engine and integrated experience
Architectural Pillars
Main-Memory Optimized
T-SQL Compiled to Machine Code
High Concurrency
SQL Server Integration
Optimized for in-memory data
Indexes (hash and range) exist only in memory
No buffer pool, B-trees
Stream-based storage
T-SQL compiled to machine code via C code generator
Invoking a procedure is just a DLL entry-point
Aggressive compile-time
Multi-version optimistic concurrency control with full ACID support
Core engine uses lock-free algorithms
No lock manager, latches or spinlocks
Same manageability, administration & development experience
Integrated queries & transactions
Integrated HA and backup/restore
Drivers
Hardware trends
Business
Steadily declining memory price, NVRAM
Stalling CPU clock rate
Many-core processors
TCO

8. Columnstore (index) Data stored as rows Data stored as columns
Benefits:
Improved compression:
Data from same domain compress better
Reduced I/O:
Fetch only columns needed
Improved Performance:
More data fits in memory C1 C2 C3 C5 C4 …

9. In-memory column store 2016
Updatable NCCI
In-Memory OLTP + Column-store
Faster batch mode scans using CPU vector instructions
Dynamic Aggregate pushdown
PK/FK enforcement
Offload Reporting to AlwaysOn Secondary Replica

10. Demo Column store performance improvement Lindsey Allen
LINEITEM: 600M rows
ORDERS: 150M rows
CUSTOMER: 15M rows
CUSTOMER_ZIP: 315M rows

11. Deeper insights across data & Hyperscale Cloud
Access any data
Scale and manage
Hybrid solutions
PolyBase
Native JSON
Temporal database support
Power Query for analytics and reporting
Built-in Advanced Analytics
Business insights through rich visualizations on any mobile device
Enterprise-grade Analysis Services
New single SSDT in Visual Studio 2015
Enhanced MDS
Enhanced SSIS
Enhanced Reporting Services
Stretch tables into Azure
Power BI with on-premises data
Hybrid scenarios with SSIS
Azure Data Factory integration with SSIS
Package Lineage and impact analysis
Connect SSIS to cloud data sources
Enhanced backup to Azure
X faster restore and 50% reduction in storage
Easy migration of on-premises SQL Server

12. Query Store
Flight data recorder for your database

13. When performance is not good…
Web site is down
Database is not working
Temporary perf. issues
Impossible to predict / root cause
DB upgraded
Regression caused by new bits
Plan choice change can cause these problems

14. With Query Store you CAN…
Long-term/strategic
Find and fix plan regressions
Identify top resource consumers
De-risk SQL Server upgrade
Deeply analyze workload patterns
Short-term/tactical

15. Demo
Fixing performance regression using Query Store
Borko Novakovic

16. Temporal Database

17. Why temporal? Real data sources are dynamic Workarounds are…
4/16/2017 3:29 PM
Why temporal?
Real data sources are dynamic
Historical data may be critical to business success
Traditional databases fail to provide required insights
Workarounds are…
Complex, expensive, limited, inflexible, inefficient
SQL Server 2016 makes life easy
No change in programming model
New Insights
© 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

18. history as a stretch table: PeriodEnd < “Now - 6 months”
Microsoft Ignite 2015
4/16/2017 3:29 PM
Facts:
History is much bigger than actual data
Retained between 3 and 10 years
“Warm”: up to a few weeks/months
“Cold”: rarely queried
SELECT * FROM Department
FOR SYSTEM_TIME
AS OF ' '
Azure SQL Database
Solution:
history as a stretch table:
PeriodEnd < “Now - 6 months”
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

19. Demo
Auditing with Temporal database
Borko Novakovic

20. Server & Tools Business
4/16/2017
Built-in advanced analytics In-database analytics
Example Solutions
Fraud detection
Sales forecasting
Warehouse efficiency
Predictive maintenance
Extensibility ? R
R Integration
Microsoft Azure Machine Learning Marketplace
New R scripts
010010
100100
010101
010010
100100
010101
Data Scientist
Analytic Library
Interact directly with data
010010
100100
010101
010010
100100
010101
Data Developer/DBA
Manage data and
analytics together
T-SQL Interface
Relational Data
Built-in to SQL Server
© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
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.

21. Demo
Build-in Advanced analytics
Lindsey Allen

22. Fisher’s Iris flower dataset
a typical test case in machine learning
Iris species can be identified based on their sepal and petal length/width
Plotting these attributes shows well differentiated classes with few overlaps
AML Gallery
ML Studio
SSMS / R
SSRS / CR
Excel / PV
Power BI.com

23. CTA [TAE8DD] Azure SQL Data Warehouse Overview
[T55A62] Microsoft Azure SQL Database: Overview
[TC530B] Stretching on-prem databases to cloud
[T4D1C9]In-Memory Technologies Overview
Polybase in SQL Server Futures - A sneak Peek
[TB63B1] In-Memory OLTP Futures
[T9F2FD] Overview of Microsoft SQL Server Security Futures
Temporal, Query Store and JSON Support in SQL Server Futures
[TCFAC2] ColumnStore Index: Microsoft SQL Server 2014 and Beyond
[TD4D79] Best Practices for Designing Your Cloud-Based, Data-Tier Strategy
[TBD345] APS and Data Warehousing in the cloud - Technical drilldown
[TB01EC] Elastic Scale for Microsoft Azure SQL Database

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4/16/2017 3:29 PM
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© 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.