Erin Dempster SQL Server 2019 Sneak Peek

Thanks to our GOLD Sponsor

Thanks to our SILVER Sponsors

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

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

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: https://info.microsoft.com/rs/157-GQE-382/images/EN-US-CNTNT-white-paper-DBMod-Microsoft-SQL-Server-2019-Technical-white-paper.pdf © 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Data Classification Demo

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: https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/always-encrypted-enclaves?view=sqlallproducts-allversions plaintext © 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Big Data Cluster Edition

Early Adoption Program SQL Server 2019 Big Data Cluster Edition in EAP only Register at https://aka.ms/eapsignup

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.

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

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 https://www.wpclipart.com/signs_symbol/love/hearts/rainbow_love_heart.png.html (Lower right) http://pluspng.com/pink-love-heart-png-hd-7132.html (Mid-right and lower left) https://en.wikipedia.org/wiki/Heart_(symbol) (remaining)

Installation Types Minikube – Single server installation Kubernetes – On premise, multi-server installation Azure Kubernetes Services (AKS)

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

Installation – mssqlctl - Initial Screen

Installation – Key Parameters ACCEPT_EULA Yes MSSQL_SA_PASSWORD S0m3P@ssw0rd STORAGE_CLASS_NAME DEFAULT CLUSTER_TYPE MINIKUBE (KUBERNETES or AKS) STORAGE_SIZE 6Gi STORAGE_POOL_STORAGE_SIZE STORAGE_SIZE

Installation – Key Parameters ACCEPT_EULA Yes MSSQL_SA_PASSWORD S0m3P@ssw0rd STORAGE_CLASS_NAME DEFAULT CLUSTER_TYPE MINIKUBE (KUBERNETES or AKS) STORAGE_SIZE 6Gi STORAGE_POOL_STORAGE_SIZE STORAGE_SIZE

Installation – Key Parameters ACCEPT_EULA Yes MSSQL_SA_PASSWORD S0m3P@ssw0rd STORAGE_CLASS_NAME DEFAULT CLUSTER_TYPE MINIKUBE (KUBERNETES or AKS) STORAGE_SIZE 6Gi STORAGE_POOL_STORAGE_SIZE STORAGE_SIZE

Installation mssqlctl cluster create –name sql2019

SQL Administration Demo

Release Timeline

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 - https://sqlserverbuilds.blogspot.com/#sql2019

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. (https://docs.microsoft.com/en-us/sql/sql-server/what-s-new-in-sql-server-ver15?view=sqlallproducts-allversions#ssas)

Questions???