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Experience SQL Server 2017: The Modern Data Platform
bobward@microsoft.com
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
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
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?
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
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”
Experience SQL Server 2017: The Modern Data Platform
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
Before
Spill Spill
After
Spill detected
and feedback
generated
• dm_db_tuning_recommendations
Detect
• and system corrects
Turn on Auto
• to “last known good”
Reverts back
Perfect to help with parameter
sniffing
Experience SQL Server 2017: The Modern Data Platform
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
Experience SQL Server 2017: The Modern Data Platform
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
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
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
Session Recommendation Scenario
Speaker
Attendee Location
Follows
From
Industry
From
Session
Presents
Attends
Track
Topic
From
From
-- 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”)
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”)
Experience SQL Server 2017: The Modern Data Platform
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
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
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
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
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
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
Experience SQL Server 2017: The Modern Data Platform
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
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.
Experience SQL Server 2017: The Modern Data Platform

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Experience SQL Server 2017: The Modern Data Platform

  • 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
  • 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.

Editor's Notes

  • #4: #1 price/performance in TPC-H non-clustered as of 9/1/2017 - http://www.tpc.org/3323 #1 TPC-H non-clustered benchmark as of 9/1/2017 - http://www.tpc.org/3323 #1 TPC-E performance as of 9/1/2017 - http://www.tpc.org/4075
  • #5: Last but not least, customers need flexibility when it comes to the choice of platform, programming languages & data infrastructure to get from the most from their data.   Why? In most IT environments, platforms, technologies and skills are as diverse as they have ever been, the data platform of the future needs to you to build intelligent applications on any data, any platform, any language on premises and in the cloud.   SQL Server manages your data, across platforms, with any skills, on-premises & cloud Our goal is to meet you where you are with on any platform, anywhere with the tools and languages of your choice. SQL now has support for Windows, Linux & Docker Containers. It allows you to leverage the language of your choice for advanced analytics – R & Python.
  • #12: Want to hear about a performance problem the next morning vs getting called in the middle of the night?
  • #16: -SQL Server is a platform for operationalizing machine learning. -What is the Best practice to work against SQL Server with ML? -Use compute context and work against SQL Server all the way from feature engineering, experimentation/evaluation to operationalization of models.
  • #18: One graph per database. Nodes and edges may have properties associated to them. Edge tables can be used to model many-to-many relationships.
  • #24: [this slide contains animations] In assessments, Data Migration Assistant (DMA) automates the potentially overwhelming process of checking database schema and static objects for potential breaking changes from prior versions. DMA also offers performance and reliability recommendations on the target server. [click] The first phase is to use DMA to assess the legacy database and identify issues. [click] In the second phase, issues are fixed. The first and second phases are repeated until all issues are addressed. [click] Finally, the database is upgraded to SQL Server 2017. For more information, see: https://blogs.msdn.microsoft.com/datamigration/2016/08/26/data-migration-assistant-how-to-assess-your-on-premises-sql-server-instance/
  • #25: Source: https://docs.microsoft.com/en-us/sql/ssma/sql-server-migration-assistant SAP ASE was formerly known as SAP Sybase ASE/Sybase.
  • #26: Source: https://azure.microsoft.com/en-gb/campaigns/database-migration/ As organizations look to optimize their IT infrastructure so that they have more time and resources to focus on business transformation, Microsoft is committed to helping to accelerate these initiatives. Microsoft have announced that a new migration service is coming to Azure to streamline customers’ journey to the cloud. This service will streamline the tasks required to move existing competitive and SQL Server databases to Azure. Deployment options will include Azure SQL Database and SQL Server in Azure VM. Managed service platform for migrating databases. Azure SQL DB and managed instance as targets. Competitive DBs—Oracle and more. Meets enterprise nonfunctional requirements (NFRs)—compliance, security, costs, and so on. Talk about the technical details: Source ->Target. Secure. Feature parity with competitors. Zero data loss and near zero downtime migration with the Azure platform service.
  • #27: 1 #1 non-clustered 1TB TPC-H (http://www.tpc.org/3331) , #1 non-clustered 10TB TPC-H (http://www.tpc.org/3329) , #1 non-clustered 30TB TPC-H (http://www.tpc.org/3321) , and #1 TPC-E (http://www.tpc.org/4081) as of November 20th, 2017.