1. Erin Dempster
SQL Server 2019 Sneak Peek

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5. About Me Pronouns: she/her
Senior Superior Consulting Services
MCSE Data & Analytics
SQL Server 2016 & 2017
Application Development
Transactional DB Development
SQL Server Administration

6. Agenda Data Classification Big Data Clusters Release Timeline
Overview
Installation
Basic Task – Restore DB
Release Timeline
Questions

7. Data classification and assessments
5/29/2019 8:05 PM
Data classification and assessments
Classification tool allows you to tag columns stored in a SQL Server database with pre- defined set of GDPR-related labels
Data Classification and auditing built-in to the engine NEW
Get visibility into your security state and meet compliance standards with SQL Server Vulnerability Assessment
SQL Data Classification Report
SQL Data Discovery and Classification allows you to classify columns in your database that contain sensitive information. You can classify columns by the type of information they contain—names, addresses, social security numbers, and so on—and by the level of sensitivity of the data in the column—including levels such as public, general, confidential, and confidential. You can easily generate reports from the classification you have applied to enable you to meet statutory and regulatory requirements, such as EU GDPR.
Vulnerability assessment— track compliance of your SQL Server instances and Azure SQL Database instances with recognized security best practices. Vulnerability assessment gives you a simple way to proactively monitor and improve your database security posture, and to better comply with data protection regulations such as EU GDPR.
New in SQL Server 2019 and Azure SQL Database, Data Classification and auditing built-in to the engine NEW
Source:
© 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

8. Data Classification Demo

9. Always Encrypted with secure enclaves protects sensitive data
5/29/2019 8:05 PM
Always Encrypted with secure enclaves protects sensitive data
In-place encryption enables cryptographic operations on sensitive data without moving the data outside the database NEW
Rich computations including pattern matching and range comparisons are supported inside the secure enclave, enabling a broad range of applications NEW
Always Encrypted with secure enclaves is enabled by Windows Server 2019
Always Encrypted with secure enclaves
plaintext
ciphertext
SQL
Enhanced client driver
Enclave
Our differentiated security feature, Always Encrypted, is enhanced in this release when running SQL19 on WS19. Until now, Always Encrypted protected the data by encrypting it on the client side and never allowing the data or the corresponding cryptographic keys to appear in plaintext inside the SQL Server Engine. As a result, the functionality on encrypted columns inside the database was severely restricted. The only operations SQL Server could perform on encrypted data were equality comparisons.
Always Encrypted with secure enclaves addresses these limitations by allowing computations on plaintext data inside a secure enclave on the server side. A secure enclave is a protected region of memory within the SQL Server process, and acts as a trusted execution environment for processing sensitive data inside the SQL Server engine. This allows for computations on cryptographic operations (initial data encryption or key rotation) and rich computations (for example, pattern matching).
Another advanced security features include Dynamic Data Masking and Row Level Security.
Link:
plaintext
© 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

10. Big Data Cluster Edition

11. Early Adoption Program
SQL Server 2019 Big Data Cluster Edition in EAP only Register at

12. Scale out big data compute and storage
5/29/2019 8:05 PM
Scale out big data compute and storage
SQL Server 2019 includes Spark and HDFS, enabling you to read and write directly in HDFS using SQL Server or Spark NEW
Elastically scale compute and storage on demand using the Kubernetes architecture NEW
Apps, BI, and analytics access all your relational and big data through the SQL Server master instance using T-SQL NEW
Scale-out data marts combine and cache data from relational and non-relational data sources for fast querying NEW
Custom apps BI
Analytics
SQL
SQL Server master instance
SQL Server
HDFS Data Node
Spark
Kubernetes pod
SQL Server
HDFS Data Node
Spark
SQL Server
HDFS Data Node
Spark
Easily scale your SQL Server and Big Data storage using HDFS-based storage pools
Enable SQL Developers to build applications consuming Enterprise Data Lakes
Enable Business Analysts to reason over ALL Data using SQL query
Enable the use of existing eco-system of SQL Server tools and Apps to access and analyze enterprise data
Eliminate the need for data movement through data virtualization and HDFS data-marts
Node
Node
Node
Persistent storage
Intelligence over all data
© 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

13. Increase analytics and apps performance
Directly read from HDFS
Persistent storage …
Storage pool
SQL Server
Spark
HDFS Data Node
Kubernetes pod
Analytics
Custom apps BI
SQL Server master instance
Node
SQL
Cluster
Compute pool
SQL Compute Node
External data sources
Data pool
SQL Data Node
Compute pool
SQL Compute Node
Storage
Compute pool
SQL Compute Node …
IoT data
Increase analytics and apps performance with scale out data pools
Intelligence over all data

14. Loving the Penguin
SQL Server 2019 Big Data Clusters runs in Linux containers with Docker. Having some familiarity with Linux will go a long way with an introduction to Big Data Clusters
(Lower right)
(Mid-right and lower left)
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15. Installation Types Minikube – Single server installation
Kubernetes – On premise, multi-server installation
Azure Kubernetes Services (AKS)

16. Installation - Effort vs Cost
Type
Effort (1 = Easy, 5 = Really Hard)
Cost
Minikube 3 $
Kubernetes – On Premise 5+ $$
Azure Kubernetes Services 1
$$$$$

17. Installation – mssqlctl - Initial Screen

18. Installation – Key Parameters
ACCEPT_EULA Yes MSSQL_SA_PASSWORD STORAGE_CLASS_NAME DEFAULT CLUSTER_TYPE MINIKUBE (KUBERNETES or AKS) STORAGE_SIZE 6Gi STORAGE_POOL_STORAGE_SIZE STORAGE_SIZE

19. Installation – Key Parameters
ACCEPT_EULA Yes MSSQL_SA_PASSWORD STORAGE_CLASS_NAME DEFAULT CLUSTER_TYPE MINIKUBE (KUBERNETES or AKS) STORAGE_SIZE 6Gi STORAGE_POOL_STORAGE_SIZE STORAGE_SIZE

20. Installation – Key Parameters
ACCEPT_EULA Yes MSSQL_SA_PASSWORD STORAGE_CLASS_NAME DEFAULT CLUSTER_TYPE MINIKUBE (KUBERNETES or AKS) STORAGE_SIZE 6Gi STORAGE_POOL_STORAGE_SIZE STORAGE_SIZE

21. Installation
mssqlctl cluster create –name sql2019

22. SQL Administration Demo

23. Release Timeline

24. SQL Server 2019 Releases1
CTP 2.0 – September 24th CTP 2.1 – November 6th CTP 2.2 – December 12th CTP 2.3 – March 1st CTP 2.4 – March 24th … Release Candidate -? RTM - ?
1 Microsoft SQL Server Versions List -

25. New to CTP 2.4 Database Engine Analysis Services Big Data Clusters
Truncation error improvements
Analysis Services
Support for Many-to-Many Relationships
Big Data Clusters
GPU Support for TensorFlow
Spark 2.4 now included
Database Engine
Error message ID 8152 has been replaced with error 2628 to now include the column and string value that would be truncated.
“String or binary string would be truncated in table <tableName>, column <columnName>. Truncated value: <value>”
Analysis Services
CTP 2.4 now allows for many-to-many relationships in tabular models. Developers can now implement relationships where the granularity of the two tables are different. One downside for the CTP…it appears the relationships can only be built through scripting APIs or Tabular Editor (Open source). This is expected to change before RTM. (

26. Questions???