And what can my audience look forward to?
A full day of diving into the latest trend in IT Technology, specifically data storage: In-Memory optimization (storage and computation). If you are still thinking traditional row-store indexes, it is time to level up. Here is your chance for a very low price to learn from the first steps unto the pitfalls of reality:
“In-Memory Technologies in SQL Server – From 0 to Operational Analytics Master”
The abstract goes as follows:
Since SQL Server 2016 Service Pack 1, most programming features have been available in all editions, including the two In-Memory technologies: Columnstore Indexes and In-Memory OLTP.
Columnstore indexes, which have been existing since SQL Server 2012 (actually PDW v2008), are mainly optimized for big amounts of data (millions of rows) and offer blazingly fast OLAP-style queries, which is made possible by their special structure (columnar storage), sophisticated compression, and batch-mode processing for much more efficient CPU-usage than traditional row-store-Queries.
The In-Memory OLTP engine, which will be the second topic of this full day, came into the product with SQL Server 2014 and has since then been extensively improved in terms of both scalability and T-SQL language support, taking away many of the relevant limitations for adaption of version 1 in a similar way as the Columnstore technology over the course of its development.
Thirdly, the so-called In-Memory Operational Analytics are supported by the possibility to create Columnstore Indexes on memory optimized tables!
All those improvements will make In-Memory technologies a viable option in many projects. For Datawarehouses, many say that Columnstore will become the default storage type for all objects in the near future. And it can be foreseen that over the years the same will happen for OLTP-tables that have to support highly concurrent workloads, which will all be based on memory optimized tables.
It’s time to extend your skills to embrace those technologies, and learn how to implement and support those new types of storage that are coming to our databases, addressing the challenge of ever more data being stored and queried and performance demands and (real time) analytic requirements going up.
During this full-day training session, Microsoft Certified Master for the Data Platform Andreas Wolter, familiar with SQL Server’s In-Memory technologies from the early bits on, will give a complete picture on the current state of technology. Attendees will learn how and where to use either In-Memory OLTP or Columnstore or even both for efficient queries and data storing, but also which problems still exist in real-world projects that sometimes make it hard to find the right solution design to profit from those technologies, and cover the important bits and pieces both from a developer’s and administrator’s perspective.
- Columnstore Storage Engine and compression internals
- What is the benefit for OLAP performance
- When to use Clustered or Nonclustered Columnstore Indexes
- XTP Engine internals for In-Memory OLTP performance benefits
- Memory optimized Tables, Indexes and Variables
- Natively compiled stored procedures & Triggers
- Combination of Row-Store, Columnstore/xVelocity and XTP engine for operational analytics
- How the new storage engines Columnstore & XTP work behind the covers
- What are the strengths and weaknesses of these alternate storage engines and how can they be played out best
- How to get a quick start with In-Memory optimized objects in almost any environment
- What are the typical performance patterns that these technologies address
- How to build highly performing Datawarehouse tables
- How to improve OLTP hotspot tables with In-Memory technologies
- How to enable real-time analytics of operational data
- What’s important from a file management perspective for administrators
- How to maintain Columnstore and In-Memory Hash- & Range-indexes
- What challenges arise from those technologies
- Performance Improvements for OLAP workloads with Nonclustered Columnstore indexes
- Clustered Columnstore indexes
- Performance Improvements for OLTP workloads with memory optimized tables, indexes and code
- Operational analytics on row store vs. operational analytics on In-Memory under different workload types
- How Columnstore indexes handle updates to data under the cover
- How In-Memory optimized objects look like on disk
Sign-up here as long as seats are available! http://dataplatformgeeks.com/dps2017/pre-conference-seminars/
After the PreCon I will give 2 more sessions at DPS 2017:
Troubleshooting Availability Groups
SQL Server Security for Developers
Also, I have been asked by KD, the founder of KDSSUG (Knowledged Dedicated SQL Server User Group) to present at their Event, “KDSSG MSSQL Tech Unite 2017” on August 20. Session topic TBD.
Next stops after that: SQLSaturday Denmark in Copenhagen October 7 with another full day PreCon Oct. 6th: “Practical Performance Monitoring & Troubleshooting”. Save the date and register soon as my previous events on that subject have quickly filled up.
The choice is yours