The document discusses the challenges of modern data platforms including disparate systems, multiple tools, high costs, and siloed insights. It introduces the Microsoft Data Platform as a way to manage all data in a scalable and secure way, gain insights across data without movement, utilize existing skills and investments, and provide consistent experiences on-premises, in the cloud, and hybrid environments. Key elements of the Microsoft Data Platform include SQL Server, Azure SQL Database, Azure SQL Data Warehouse, Azure Data Lake, and Analytics Platform System.
3. • Disparate systems and processes
• Multiple tools and skillsets
• High cost of ownership
• Siloed insights on disconnected data
• Costly data movement and delay
Challenges of the Modern Data Platform
Fragmented architectures are inefficient
AnalyticsVisualization
Relational in the cloud
Analytics Visualization
Hadoop
{ }
NoSQL Data Lake
AnalyticsVisualization
Relational DBAppliance
Analytics Visualization
Hadoop Appliance
CloudOn-premises
Relational Non-relational
4. Azure SQL Database
Azure SQL Data Warehouse
SQL Server 2016 on VM
Analytics Platform System
Azure Data Lake
SQL Server 2016
Analytics Platform System
SQL
Relational Non-relational
On-premisesCloudMicrosoft Data Platform
Transforming data into intelligent action
• Manage all your data in a mission critical,
scalable, secure way
• Gain deep insights across all of your data
without data movement
• Utilize existing skills and investments
• Consistent on-premises, cloud and hybrid
experiences
Federated query
Business intelligence
Machine learning &
advanced analytics
Insights
7. Continuous Innovation
End-to-end mobile BI
Advanced Analytics
Enterprise-grade DW
Mission critical OLTP
The best
SQL Server
release in history
SQL Server 2016
Speed
Agility
Proven
Feedback
SQL DB SQL DB SQL DB SQL DB
New innovations
Across customer base
Cloud-First Approach + DevOps
Continuous
enhancements
Hybridcloud
8. National Institute of Standards and Technology Comprehensive Vulnerability Database update 12/2016.
Everything built-inTPC-H
Oracle
is #5#2
SQL Server
#1
SQL Server
#3
SQL Server
The Power of SQL Server
Everything built-in
June 2016
SQL Server 2016
TPC-E
0 1
4
0 0
3
0
34
29
22
15
5
22
16
6
43
20
69
18
49
74
3
0
10
20
30
40
50
60
70
80
2010 2011 2012 2013 2014 2015 2016
SQL Server Oracle MySQL2 SAP HANA
1/12
9. Only data solution to
encrypt your data at
rest and in motion
Connect your
relational data to
big data with PolyBase
Real-time operational
analytics without
impacting performance
Up to 30x faster
transactions, 100x faster
queries with InMemory
Unparalleled choice
for developer tools
and languages
1 T-SQL
Java
C/C++
C#/VB.NET
PHP
Node.js
Python
Ruby
For all your applications
Innovations across all editions
Available now
SQL Server 2016 SP1
10. On the platform of your choice
SQL Server v.Next
Targeting CY2017
SQL Server v.Next GA*
SQL Server v.Next Public Preview available now on Linux, Windows, and Docker.
11. Just Runs Faster
Core Engine Scalability
Automatic Soft NUMA
Dynamic Memory Objects
SOS_RWLock
Fair and Balanced Scheduling
Parallel INSERT..SELECT
Parallel Redo
DBCC
DBCC Scalability
DBCC Extended Checks
TempDB
Goodbye Trace Flags
Setup and Automatic Configuration of Files
Optimistic Latching
I/O
Instant File Initialization is No Longer Hidden
Multiple Log Writers
Indirect Checkpoint Default Just Makes Sense
Log I/O at the Speed of Memory
Spatial
Native Implementations
TVP and Index Improvements
Columnstore
Batch Mode and Window Functions
Always On Availability Groups
Turbocharged
Better Compression and Encryption
12. Persisted Log Buffer
The evolution of storage
HDD SSD (ms)
PCI NVMe SSD (μs)
Tired of WRITELOG waits?
Along comes NVDIMM(ns)
Windows Server 2016 supports block storage
(standard I/O path)
A new interface for DirectAccess (DAX) Persistent
Memory
(PM)
Watch these
videos
Channel 9 on
SQL and PMM
NVDIMM on
Win 2016 from
build
Format your NTFS
volume with /dax
on Windows
Server 2016
Create a 2nd tlog
file on this new
volume on SQL
Server 2016 SP1
Tail of the log is
now a “memcpy”
so commit is fast
WRITELOG waits =
0 ms
here
13. Mission critical platform Deeper Insights Hyperscale
In-Memory OLTP
Greater T-SQL surface area, terabytes of
memory supported, and higher number of
parallel CPUs
Query Store
A flight data recorder for your database
Always Encrypted
Sensitive data remains encrypted at all times,
with ability to query
Row-Level Security
Fine-grained access control for table rows
Enhanced Always On
Distributed Availability Groups, Basic
Availability Groups, Automatic Failover
The richest set of diagnostics in the
industry. Read more here
14. High-Performance Execution Engines
ColumnStore + Batch
Mode Execution
• Columnar compression to save
space in memory and on disk
• New execution engine that
optimizes instructions/row and
minimizes CPU data bus I/O stalls
• Often gives speedups of 10x
• Allows you to store, manage, and
gain value out of significantly more
data
In-Memory OLTP Engine
Model
• Lock-free algorithms
• Optimistic concurrency model
• Full transactional support
• Compiled procedures
• Can give significant speedups (2x-
50x) on high-end OLTP applications
Capturing technical breakthroughs in two areas
These enable you to write SQL and leverage ever-
increasing performance for your applications
MissionCriticalPlatform
15.
16. Secure Code
• Secure development lifecycle
• Least vulnerable last 6 years
Most Secure Database
Secure engine
Least vulnerable last 6 years
0 2
11
8
0 1
4
0 0
3
69
53 53 55
34
29
22
15
5
22
5
28
25
29
21
6
13
3
0
6
16 16
9 8 6
43
20
69
18
49
3
0
10
20
30
40
50
60
70
80
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
SQL Server Oracle DB2 MySQL SAP HANA
* National Institute of Standards and Technology Comprehensive
Vulnerability Database update 10/2015
while being most utilized
MissionCriticalPlatform
17. Most Secure Database
Surrounded by layers of protection
Secure Code
• Secure development lifecycle
• Least vulnerable last 6 years
• SQL Threat Detection
• SQL Server Auditing
• Row-level Security
• Dynamic Data Masking
• Always Encrypted
• Transparent Data Encryption
• Encryption-in-flight
Control Access
• SQL Authentication
• Windows Authentication
• Azure Active Directory Auth.
Monitor activity
Control access
Protect data
Come to the instructor lead
security lab at 4:45 pm today!
MissionCriticalPlatform
18. trust boundary
"SELECT Name FROM Customers
WHERE SSN = @SSN","111-22-3333"
Always Encrypted
Protect data at rest and in motion, on-premises and in the cloud
Name
Wayne Jefferson
ADO .NET
Name
0x19ca706fbd9a
Result SetResult Set
Client
Name SSN Country
0x19ca706fbd9a 0x7ff654ae6d USA
SQL Server or SQL Database
"SELECT Name FROM Customers
WHERE SSN = @SSN",0x7ff654ae6d
ciphertext
Encrypted sensitive data and corresponding keys
are never seen in plaintext in SQL Server
dbo.Customers
ciphertext
Security
MissionCriticalPlatform
19. Optimizing query performance and costs
Query Store = flight data recorder for databases
Built-in query monitoring
• Negligible perf & storage overhead
• Survives failover, memory pressure, …
• Data ready when that incident happens
T-SQL interface and SSMS UX
Top insights into your workload
• Query and resource stats
• Query plans
Developer
App User
Azure
application On-premise
Developer needs to find and fix
the underlying problem, ASAP
Customer reports the issue
(app is slow/unresponsive)
MissionCriticalPlatform
20.
21. Improved Always On Availability Groups
• 3 Replicas for Automatic Failover
• Database Failure Detection
Higher
Availability
• Support for Column-store Indexes
• Load Balancing of Read Workloads
More Powerful
Readable
Secondaries
• 4X Synchronization ThroughputScalability
• Different Windows Clusters
• Different Windows Domains
Flexibility
• Basic Availability Groups in
Standard Edition
Licensing
Always On Turbocharged
MissionCriticalPlatform
22. Mission critical platform Deeper Insights Hyperscale
Real-time operational analytics
Running of analytical workloads concurrently
with OLTP workloads
R Integration
Insights from data across SQL Server and
Hadoop with the simplicity of T-SQL
PolyBase
Insights from data across SQL Server and
Hadoop with the simplicity of T-SQL
Mobile BI
Mobile reports on SSRS with Mobile Report
Publisher
Temporal Tables, JSON
Track change history, integrate with modern
service easily
23. 0100101010110 SQL Server
OLTP
SQL Server
data warehouse
ETL
In-memory
ColumnStore
In-memory
OLTP
Real-time fraud
detection
Operational analytics
Single system for OLTP and real-time analytics
Fraud detected
2-24
hrs
DeeperInsights
24. Data Scientist
Interact directly with data
Built-in to SQL Server
Data Developer/DBA
Manage data and
analytics together
Built-in advanced analytics
Running R algorithms at massive data scale
Example Solutions
• Salesforecasting
• Warehouse efficiency
• Predictive maintenance
Relational Data
Analytic Library
T-SQL Interface
Extensibility
?
R
RIntegration
010010
100100
010101
Microsoft Azure
Marketplace
New R scripts
010010
100100
010101
010010
100100
010101
010010
100100
010101
010010
100100
010101
010010
100100
010101
• Credit risk protection
DeeperInsights
25. PolyBase
Query relational and non-relational data with T-SQL
T-SQL query
SQL Server Hadoop
Quote:
************************
**********************
*********************
**********************
***********************
$658.39
Jim Gray
Name
11/13/58
DOB
WA
State
Ann Smith 04/29/76 ME
DeeperInsights
26. Support for Temporal Data
Track historical data
DeeperInsights
• Data changes over time (!)
• Databases naturally provide
a current view
• But an historical perspective
is often critical
Time travel
Data audit
Predictive analytics
Repair record-level corruptions
27.
28. Mission critical platform Deeper Insights Hyperscale
Stretch Database
Stretch operational tables in a secure manner
into Azure for cost-effective historic data
availability.
Enhanced backup to Azure
Faster restore times, 50% reduction in storage.
Larger DBs
29. 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
Sue Daniels ypo85ba616rj 5/12/2005
Sarah Jones bns51ra806fd 5/22/2005
Jake Marks mci12hh906fj 6/07/2005
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
Stretch SQL Server into Azure
Stretch cold data to Azure with remote query processing
App
Query
Microsoft Azure
Jim Gray ox7ff654ae6d 3/18/2005
HyperscaleCloud
31. Fully managed Database Service …
So you can focus on your Business
• Built for SaaS and Enterprise applications
• Predictable performance & Pricing
• Elastic database pool for unpredictable SaaS workloads
• 99.99% availability built-in
• Geo-replication and restore services for data protection
• Secure and compliant for your sensitive data
• Fully compatible with SQL Server 2016 databases
32. Predictable workloads
Single databases or partitioned data across multiple
databases; scale between service tiers and
performance levels as capacity needs fluctuate.
Scaledatabases
upasneeded
Scale out/in the pool
…
Single database or
partitioned databases
Customer
1
Customer
2
Customer
3 Customer
#N…
Unpredictable workloads
For large numbers of databases with unpredictable
performance demands; pool resources to be shared
between these databases.
Elastic Database Pool
Databasesconsume
resourcesasneeded
Managing large numbers of Databases
33. SQL Database Service Tiers (single DB model)
*The 99.99% availability SLA does not apply to the existing Web and Business editions, which will continue to be supported at 99.9% availability.
Built For
Available SLA
Database Max Size
Business Continuity
Security
Performance Objectives
Database Transaction
Units (DTUs)
Available Tiers
($/Month) and GA Price
Point-in-time Restore
(“oops” Recovery)
BASIC PREMIUMSTANDARD
P1S0
Light transactional workloads Medium transactional workloads Heavy Transactional Workloads
99.99%*
2 GB 250 GB 500 – 1,000 GB (more soon)
Any point within 7 days Any point within 14 days Any point within 35 days
Geo-restore
Geo-replication, standby
secondary
Active geo-replication, up to four readable
secondary backups
Auditing, row-level security, dynamic data masking, encryption
Transactions per hour Transactions per minute Transactions per second
5
$4.99
S1 S2 S3 P2 P4 P6 P11
10 20 50 100
$15 $30 $75 $150
125 250 500 1,000 1,750
$465 $930 $1,860 $3,720 $7,001
P15 …
4,000
$16,003
34. Azure SQL Data Warehouse
• A relational data-warehouse-as-a-service, fully managed by Microsoft.
• Industries first elastic cloud data warehouse with proven SQL Server capabilities.
• Support your smallest to your largest data storage needs.
Saas
Azure
Public
Cloud
Office 365Office 365
AzureAzure
35.
36. Source
Target
Windows Azure
Windows Azure
Tool(s) DMA DMA SSMA
Legacy
Modern
Comparison
Reports
A’
SQL 2008 Instance
Extensive
tracing
Statistical
Analysis
Analyze
Results
B
SQL 2016 Instance
Extensive
tracing
capture prod
workload
37. Migrations by Industry
Financial Services 139
Discrete Manufacturing 122
Retail &
Consumer Goods
113
Government 105
Health 94
Professional Services 93
Process Manufacturing
& Resources
59
Hospitality & Travel 44
Telecommunications 36
Power & Utilities 31
Other Industries 119
TOTAL 955
38. Azure SQL Database
Azure SQL Data Warehouse
SQL Server 2016 on VM
Analytics Platform System
Azure Data Lake
SQL Server 2016
Analytics Platform System
SQL
Relational Non-relational
On-premisesCloudMicrosoft Data Platform
Transforming data into intelligent action
• Manage all your data in a mission critical,
scalable, secure way
• Gain deep insights across all of your data
without data movement
• Utilize existing skills and investments
• Consistent on-premises, cloud and hybrid
experiences
Federated query
Business intelligence
Machine learning &
advanced analytics
Insights
43. In-Memory Transactional Processing
SQL Server Integration
• Same manageability,
administration &
development experience
• Integrated queries &
transactions
• Integrated HA and
backup/restore
In-Memory Data
Access
• Indexes (hash and range)
exist only in memory
• Records exist only in
memory (pointers from
indexes)
• No buffer pool, B-trees
• Stream-based storage
T-SQL Compiled to
Machine Code
• T-SQL compiled to machine
code via C code generator
• Invoking a procedure is just
a DLL entry-point
• Aggressive optimizations @
compile-time
Declining memory price Many-core processorsStalling CPU clock rate Lower TCO
Hardware trends Business
Integrated experience
High performance data
operations
Efficient business-logic
processing
Customer
Benefits
ArchitecturalPillarsDrivers
High Concurrency
• Core engine uses lock-free
algorithms
• No lock manager, latches or
spinlocks
• Multi-version optimistic
concurrency control with full
ACID support
Frictionless scale-up
44. 45
Column-Store Indexes
Improved compression:
Data from same domain
compress better
Reduced I/O:
Fetch only columns needed
…
Row-store indexes Column-store indexes
Ideal for OLTP
Efficient operation on small set of rows
C5C1 C2 C3 C4
Improved Performance:
More data fits in memory
Optimized for CPU utilization
Ideal for DW Workload
48. • Interchange data with apps
and services
• Exploit agility of NoSQL to
easily extend your app
SQL Server
Web app, service
49. CREATE TABLE Departments
(
DeptId int NOT NULL PRIMARY KEY CLUSTERED
, DeptName varchar(50) NOT NULL
, ManagerId int NULL
)
;
How Temporal Tables Work
End-to-endmobileBI
50. CREATE TABLE Departments
(
DeptId int NOT NULL PRIMARY KEY CLUSTERED
, DeptName varchar(50) NOT NULL
, ManagerId int NULL
, SysStartTime datetime2 GENERATED ALWAYS AS ROW START NOT NULL
, SysEndTime datetime2 GENERATED ALWAYS AS ROW END NOT NULL
, PERIOD FOR SYSTEM_TIME (SysStartTime, SysEndTime)
)
WITH (SYSTEM_VERSIONING = ON (HISTORY_TABLE = DepartmentHistory))
;
How Temporal Tables Work
End-to-endmobileBI
51. How Temporal Tables Work
Insert
prior version Start EndDeptId DeptName ManagerId
DepartmentsHistory
End-to-endmobileBI
Update / Delete
Departments (temporal)
Departments
Start EndDeptId DeptName ManagerId
52. How Temporal Tables Work
Start EndDeptId DeptName ManagerId
DepartmentsHistory
End-to-endmobileBI
Normal query
SELECT * FROM Departments
GO
Departments (temporal)
Departments
Start EndDeptId DeptName ManagerId
53. How Temporal Tables Work
Start EndDeptId DeptName ManagerId
Departments DepartmentsHistory
End-to-endmobileBI
Temporal query SELECT * FROM Departments
FOR SYSTEM_TIME AS OF '2015.01.01'
GO
Departments (temporal)
Start EndDeptId DeptName ManagerId
54. Paginated reports
Design beautiful documents using updated
tools and new features
Mobile reports
Create responsive, interactive reports optimized
for mobile devices
Modern web portal
Consume both types of reports in one web
portal using modern browsers
SQL Server Reporting Services
55. SQL Server Analysis Services 2016
Easily create models
IT pro
Increase adoption
Business analyst
Share insights faster
Faster time
to insight
BI consumers
56.
57. OLTP
Industry leading TCO
$648K
+ $120
per user for Power BI
SQL Server 2016
ADVANCED ANALYTICS
BUSINESS INTELLIGENCE
OLTP
DATA WAREHOUSING
3.4x
20x
per user
$2.2M
+ $2,230
per user for BI
Note: For OLTP and DW scenario, the price comparison
is based on a server with 2 proc, 8 cores each
Built-in with SQL Server vs.
expensive add-ons with Oracle
Complete mobile BI
In-memory
End-to-end security
Advanced Analytics
built-in
built-in
built-in
built-in
DATA WAREHOUSING
BUSINESS INTELLIGENCE
ADVANCED ANALYTICS
58. Easy with SQL Server migration assistants
SSMA for Oracle
SSMA for Sybase
SSMA for DB2
SSMA for MySQL
SSMA for Access
Hinweis der Redaktion
SQL Server is the new industry leader and SQL Server 2016 is packed with value for customers and as with our history, that value is built-in to a single enterprise sku with no additional add-ons.
Let’s take a look at the top 5 reasons why you want to bet your business needs on SQL Server. If you are on SQL Server 2005 there is no better time to modernize your apps. If you are on Oracle or IBM, no better time to look again at the value you can gain today at a much lower TCO.
<click>
Industry leader in mission critical OLTP
In case you missed, there is a new leader in Gartner’s core database MQ, where SQL Server for the first time has de-throned Oracle in both execution and vision! Microsoft SQL Server has been the industry leader for two years in a row! Customers are realizing the value that Microsoft is delivering at a rapid pace and in a customer friendly way by building-in innovation verses requiring add-ons.
SQL Server also has #1 rankings across a number of TPC-E and TPC-H performance benchmarks
Speaking of security and performance, let’s take a look at how we fair against the competition.<click>
Most secure database
SQL Server continues to be the least vulnerable database 6 years in a row. NIST (National Institute of Standards and Technology) tracks database vulnerabilities and shows SQL as the lowest even though we have more units deployed in production than both Oracle and IBM combined. So what does that mean, if you look at the chart you will see Oracle has many more vulnerabilities, this doesn’t mean that Oracle didn’t address them, but until the vulnerability patch is released and you implement it your data is at risk. Fewer vulnerabilities means fewer patches and your data is less exposed to attack.
In addition, SQL Server 2016 delivers layers of protection with capabilities that can protect your data at rest and in motion, even in the memory buffer pool, without impacting database performance, along with the ability to control access and monitor threats. This multi-layered approach combined with proven track record of being least vulnerable provide you with the most secure database on the planet. <click>
Highest performing data warehouse
From a performance perspective, looking at TPC-H a standard benchmark particularly for Data Warehousing workloads, SQL holds the number #1, #2, and #3 spots for non-clustered scale up performance on multiple hardware platforms including HP, Lenovo and Cisco and for multiple data sizes including 1TB, 3TB and 10TB. Oracle comes in at #4. This not only showcases SQL Server performance, but performance at scale for data warehousing.
SQL Server 2016 can scale from data marts to the biggest DW workloads. With SQL Server 2016 enterprise you also get the rights to deploy our scale out MPP (massive parallel processing) data warehousing appliance, so again incredible value out of a single sku. <click>
End to end mobile BI on any device
Now let’s take a look at end to end mobile BI solution. Many of you may have heard about the Datazen acquisition we made to provide our customer with mobile BI on any device. Well in SQL Server 2016 this will be integrated into Reporting Services, which we are enhancing in a big way. What this means is you can now publish modern reports using PowerBI or Excel 2016 to an iPhone, Android phone, as well as Windows phone. Best of all its built-in so no need to buy a separate product. With the new integration of Power BI and SQL Server you can enable self-service BI in addition to mobility. Even if you choose to enable self-service BI you are doing it at a fraction of the cost of Tableau and Oracle. Even though Tableau has added mobile it’s only iOS and not Android, which is important outside of the US and Tableau is only a point solution for BI, where as SQL Server can tackle all data workloads give you BI and Advanced Analytics built-in. <click>
In-database Advanced Analytics
Many customers are exploring going beyond BI into predicative analytics where they want to proactively pave their businesses future with data rather than react to data. With SQL Server 2016 you can now accomplish this with built-in in-database advanced analytics. Again the key here is in-database, because when you talk to customers trying to implement advanced analytics the number one challenge is moving the data out of your database to do perform open source R models. In addition, customers want to perform analysis using R models on the latest data which you can do quickly by combining R with SQL Server in-memory technology. With 2016 you can perform R models directly in the database. In addition, customer want to run their R models on the latest data and you can do this quickly with SQL Server 2016 by combining the power of open source R with SQL Server in-memory technology for incredibly fast reads and writes. <click>
In-memory across workloads
In addition to these top 5 reasons, our optimized in-memory technology is fueling performance across all workloads from our in-memory OLTP that provides up to 30x transactional performance to our in-memory columnstore that give over 100x faster queries for data warehouse and BI workloads. Now with SQL Server 2016, you also have the ability to combine in-memory technologies to give you super-fast reads on top of super-fast writes to enable real-time operational analytics.<click>
Consistent Experience from on-premises to cloud
In addition to in-memory across all of these workloads, we can also deliver these capabilities with a consistent experience both on-premises and cloud with common development and management tools and common T-SQL. Our goal is to provide you a great experience with data no matter where you choose to implement it! <click to next slide>
With SQL Server 2016 Service Pack 1, innovative features are now available across editions, so companies can scale across editions with a consistent programming surface area.
With SQL Server v.Next, now in public preview, and generally available to purchase targeting mid-calendar year 2017, the power of SQL Server is available on the platform of your choice.
Follow instructions in inmem_oltp\readme.txt directory
1 min
TODO: Add in resources
MSFT delivers the leading total cost of ownership (TCO) for Tier 1 workloads. Slide shows a comparison with Oracle. Key point - we are building things in while Oracle is adding things on.
Oracle ULA (unlimited license agreement) is based on enterprise SKU but it doesn’t include in-memory, advanced analytics. Add-ons can grow to as much as $10K per core
Also consider TCO over time – what future products will be packaged as add-ons from Oracle vs built-in from Microsoft? Better bet with MSFT.
<click>