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OregonSQL - November Meeting - HiHo! HiHo! SQL Server on Linux, we go!

1515 SW 5th Street
Portland, OR 97201, United States (map)

Doors will be open at 6:00 PM. Snacks will be provided.



Janis Griffin

HiHo! HiHo! SQL Server on Linux, we go!

Are you being forced to the ‘Cloud’ to reduce costs? SQL Server 2017 now runs on Windows, Linux, and Docker containers.

Now SQL Server can be installed on Linux in order to provide a consistent database platform across Window and Linux servers, as well as on-premises and in the cloud. This presentation will discuss the advantages of using SQL Server on Linux, comparing architecture, cost and performance. Several demonstrations on installing and maintaining SQL Server on different Linux distributions and Docker will be shown, as well as best practice considerations for production/development environments. Also, several useful Linux commands for monitoring, managing and backing up SQL Server will be demonstrated. Finally, client connectivity and tools will be discussed – plus the new Azure Data Studio UI with the ability to add monitoring widgets will be demonstrated.

Alfred Burnett

Simplify Database Performance and Management

Database management is complex. Database professionals are increasingly being asked to manage not only larger numbers of database instances, but multiple database platforms. Open source and NoSQL databases along with cloud adoption are all having a major impact, and DBAs are now expected to ensure the best performance and stability of this cross-platform database environment. But what if you could meet growing demands faster and with less risk? This means you’d get more time to innovate and focus on important projects. In this session, you’ll learn how to proactively manage all your database platforms from end to end. Items of discussion include: · Scoring optimal availability and performance out of Enterprise and Standard edition databases · Managing hundreds of database instances with ease · Maintaining databases both on-premises and in the cloud · Decreasing overhead by managing databases with little to no impact on performance