This is an overview of SQL Server 2017 and its features and capabilities. You can get the recording at https://youtu.be/qgSEwpaRul0

2. bobward@microsoft.com

3. End-to-end mobile BI
on any device
Choice of platform
and language
Most secure
over the last 7 years
0
20
40
60
80
100
120
140
160
180
200
Vulnerabilities(2010-2016)
A fraction of the cost
Self-serviceBIperuser
Only commercial DB
with AI built-in
Microsoft Tableau Oracle
$120
$480
$2,230
Industry-leading
performance
1/10
Most consistent data platform
#1 TPC-H performance
1TB, 10TB, 30TB
#1 TPC-E performance
#1 price/performance
T-SQL
Java
C/C++
C#/VB.NET
PHP
Node.js
Python
Ruby
R
R and Python + in-memory
at massive scale
S Q L S E R V E R 2 0 1 7
I N D U S T R Y - L E A D I N G P E R F O R M A N C E A N D S E C U R I T Y N O W O N L I N U X A N D D O C K E R
Private cloud Public cloud
+ T-SQL
In-memory across all workloads
1/10th the cost of Oracle

4. F L E X I B L E , R E L I A B L E
D ATA M A N A G E M E N T
SQL Server on the platform of
your choice
Support for RedHat Enterprise Linux
(RHEL), Ubuntu, and SUSE Enterprise
Linux (SLES)
Linux and Windows Docker containers
Windows Server / Windows 10
Choice of platform and language

5. Windows Linux
Developer, Express, Web, Standard, Enterprise  
Database Engine  
Integration Services  
Analysis Services, Reporting Services, MDS, DQS 
Maximum number of cores Unlimited Unlimited
Maximum memory utilized per instance 12 TB 12 TB
Maximum database size 524 PB 524 PB
Basic OLTP (Basic In-Memory OLTP, Basic operational analytics)  
Advanced OLTP (Advanced In-Memory OLTP, Advanced operational analytics)  
Basic high availability (2-node single database failover, non-readable secondary)  
Advanced HA (Always On - multi-node, multi-db failover, readable secondaries)  
Security
Basic security (Basic auditing, Row-level security, Data masking, Always Encrypted)  
Advanced security (Transparent Data Encryption)  
HADR
Always On Availability Groups
Failover Clustering
 
Replication 
Data
warehousing
PolyBase2 
Basic data warehousing/data marts (Basic In-Memory ColumnStore, Partitioning, Compression)  
Advanced data warehousing (Advanced In-Memory ColumnStore)  
Tools
Windows ecosystem: Full-fidelity Management & Dev Tool (SSMS & SSDT), command line tools  
Linux/OSX/Windows ecosystem: Dev tools (VS Code), DB Admin GUI tool, command line tools  
Developer
Programmability (T-SQL, CLR, Data Types, JSON)  
Windows Filesystem Integration - FileTable 
BI & Advanced Analytics
Basic Corporate Business Intelligence (Multi-dimensional models, Basic tabular model) 
Basic “R” integration (Connectivity to R Open, Limited parallelism for ScaleR) 
Advanced “R” integration (Full parallelism for ScaleR) 
Hybrid cloud Stretch Database 
What’s in SQL Server On Linux?

6. SQL Server Linux Architecture
LibOS (Win API and
Kernel)
Host Extension mapping to OS system calls
(IO, Memory, CPU scheduling)
SQLOS (SQLPAL)
SQL PAL
Everything else
System Resource &
Latency Sensitive Code
Paths
SQL Platform
Abstraction Layer (SQLPAL)
Linux Kernel
SQLSERVRSQLAGENT
ABI
API
Linux APIs (mmap, pthread_create, …)
Linux
Process
(Ring 3)
Ring 0
Based on Microsoft
Research
Drawbridge Project

7. Docker Containers: What and why?
• Docker: Multi-platform container engine
based on Linux and Windows Containers.
• NOT virtualization
• Image
• lightweight, stand-alone, executable package
that includes everything needed to run a piece
of software, including the code, a runtime,
libraries, environment variables, and config files
• Container
• runtime instance of an image—what the image
becomes in memory when actually executed
• Imagine a world of “database containers”

9. The World Leader in TPC-H and TPC-E Performance Benchmarks
World’s First Enterprise-Class “Diskless Database”
Adaptive Query Processing
Query Store Wait Statistics
Automatic Tuning
result

10. Before
Spill Spill
After
Spill detected
and feedback
generated

11. • dm_db_tuning_recommendations
Detect
• and system corrects
Turn on Auto
• to “last known good”
Reverts back
Perfect to help with parameter
sniffing

13. M I S S I O N C R I T I C A L
AVA I L A B I L I T Y O N
A N Y P L AT F O R M
Always On cross-platform
capabilities
HA and DR for Linux and Windows
“Clusterless” Availability Groups
Ultimate HA with OS-level redundancy
and low-downtime migration
Load balancing of readable secondaries

15. In-database Machine Learning
Develop Train Deploy Consume
Develop, explore and
experiment in your
favorite IDE
Train models with
sp_execute_external_
script and save the
models in database
Deploy your ML scripts
with sp_execute_external_
script and predict using
the models
Make your app/reports
intelligent by consuming
predictions

16. SQL Server Machine Learning Services
SQL Server 2016
• Extensibility
Framework
• R Support (3.2.2)
• Microsoft R Server
SQL Server 2017
• R Support (3.3.3)
• Python Support
(3.5.2)
• Native Scoring using
PREDICT
• In-database Package
Management
Azure SQL DB
• Native scoring using
PREDICT
• R Preview Coming
Soon
• Python Support in 2018

17. SQL Server 2017 – Graph Extensions
• Graph – collection of node and edge tables
• DDL Extensions – create node/edge tables
• Properties associated with Node and Edge tables
• All type of indexes are supported on node and edge
tables.
• Query Language Extensions – New built-in: MATCH, to
• support pattern matching and traversals
• Tooling and Eco-system

18. Session Recommendation Scenario
Speaker
Attendee Location
Follows
From
Industry
From
Session
Presents
Attends
Track
Topic
From
From

19. -- Find the other sessions that these other users attended
other_sessions AS
(
SELECT at.name AS attendee_name, s.name AS session_name,
COUNT(*) AS other_sessions_attended
FROM Conference.Attendee_1 AS at
JOIN Conference.SessionAttendee AS sa ON
sa.AttendeeID = at.AttendeeID
JOIN Conference.Sessions AS s ON s.SessionID =
sa.SessionID
JOIN OTHER_USR AS ou ON ou.attendeeid = at.attendeeid
WHERE s.sessionid <> 101
GROUP BY at.name, s.name
)
-- Recommend to the current user the top sessions from the
-- list of sessions attended by other users
SELECT TOP 10 s.name, COUNT(other_sessions_attended)
FROM OTHER_SESSIONS AS os
JOIN sessions AS s on s.name = OS.session_name
GROUP BY s.name
ORDER BY COUNT(other_sessions_attended) DESC;
WITH Current_Usr AS
(
SELECT AttendeeID = 6
,SessionID = 101 -- Graph session
,AttendeeCount = 1
) ,
-- Identify the other users who also attended the
-- graph session
Other_Usr AS
(
SELECT at.attendeeID, s.sessionid,
COUNT(*) AS Attended_by_others
FROM Conference.Attendee_1 AS at
JOIN Conference.SessionAttendee AS sa ON
sa.AttendeeID = at.AttendeeID
JOIN Conference.Sessions AS s ON
s.SessionID = sa.SessionID
JOIN Current_Usr AS cu ON cu.SessionID = sa.SessionID
WHERE cu.AttendeeID <> sa.AttendeeID
GROUP BY s.sessionid, at.attendeeid
) ,
Session Recommendations (“Before”)

20. SELECT
TOP 10 RecommendedSessions.SessionName
,COUNT(*)
FROM
Sessions
,Attendee
,Attended AS AttendedThis
,Attended AS AttendedOther
,Sessions AS RecommendedSessions
WHERE
Session.Session_ID = 101
AND MATCH(RecommendedSessions<-(AttendedOther)-Attendee-(AttendedThis)->Sessions)
AND (Sessions.SessionName <> RecommendedSessions.SessionName)
AND Attendee.attendeeID <> 6
GROUP BY RecommendedSessions.SessionName
ORDER BY COUNT(*) DESC;
GO
Session Recommendations with SQL Graph (“After”)

22. In-Memory OLTP Enhancements
Columnstore Index Enhancements
Resumable Online Index Rebuild
SELECT INTO.. ON < Filegroup >
New DMVs and enhancements
Indirect checkpoint improvements
And more….
Smart backup

23. Legacy SQL Server instance
DMA: Assess and upgrade schema
1. Assess and identify issues
2. Fix issues
3. Upgrade database
Data Migration Assistant
SQL Server 2017
Database
Experimentation
Assistant (DEA) to
compare perf

24. Migrating to SQL Server 2017 from other platforms
Oracle
SAP ASE
DB2
Identify apps
for migration
Use migration
tools and partners
Deploy to
production
SQL Server
Migration Assistant
Global partner
ecosystem
AND
SQL Server 2017
on Windows
SQL Server 2017
on Linux
OR

25. Oracle SQL
SQL DB
Azure Database Migration Service
Accelerating your journey to the cloud
• Streamline database migration to Azure SQL
Database (PaaS)
• Azure VM target coming
• Managed service platform for migrating databases
• Migrate SQL Server and third-party databases to
Azure SQL Database

26. SQL Server on Linux and Docker
Leader in TPC-H and TPC-E Performance1
Adaptive Query Processing and Automatic Tuning
Availability Groups without Clusters
Python and Native PREDICT for Machine Learning Services
Graph Database
A bunch of engine enhancements
Integration Services enhancements
Analysis Services enhancements

27. Experience SQL Server 2017: Start your journey here
What’s New in SQL Server 2017
Download SQL Server 2017
Getting started with SQL Server on Linux
Getting started with SQL Server on Docker
SQL Server Blog
ZDNet Review of SQL Server 2017

29. World’s First Scalable Persistent Memory Database Server
An Enterprise-Class SQL Server “Diskless Database”
HPE Scalable Persistent Memory on the HPE ProLiant DL380
Gen10
Microsoft SQL Server 2017 for Linux
SQL Server “Diskless Database”
SUSE SLE 12sp3 Operating System
Persistent Memory OS technology
Up to 45% performance improvement with Data Analytics workloads2
Up to 50%
reduction in
hardware costs1
Up to 85%
reduction in rack
space1
1 Based on a comparison between the hardware of the DL380 Gen10 server and the TPC-H @ 1,000GB hardware for the DL380 Gen9 server. See http://tpc.org/3327 2 Based on HPE internal testing on a TPC-H like benchmark, Oct. 2017.
© Copyright 2017 Hewlett-Packard Enterprise Development LP. The information contained herein is subject to change without notice. Microsoft and SQL Server are U.S. registered trademarks of Microsoft Corporation. SUSE and SLE are registered trademarks of SUSE. TPC and TPC-H are trademarks of the Transaction Processing
Performance Council. Publication no. a00007695enw, April 2017
Watch the video

30. What is a Graph Database?
• Edges or relationships are first class
entities in a Graph Database and can
have attributes or properties
associated with them.
• A single edge can flexibly connect
multiple nodes in a Graph Database.
• You can express pattern matching and
multi-hop navigation queries easily.
• Supports OLTP and OLAP (analytics)
just like SQL databases.