“There is no such thing as a SQL Server team anymore.
There is, in fact, no code base called SQL Server.
There’s only one code base, which is the Azure database code base.”
President of the Microsoft Server and Tools Division
In this article we continue sharing DB Best team experience in cloud technologies, and will focus specifically on the application back-end development and deployment to Microsoft Azure using a case study of an E-Commerce project developed by DB Best team. (more…)
At first database migration from SQL Server to SQL Azure may seem like a pretty easy thing to do. In fact when it comes to a small project of around 20 tables and about a dozen of stored procedures, this really is the case. However if you get a project of hundreds of tables, stored procedures, functions and triggers, if cross-database access is being used, and there is dynamic objects creation, then you will have to face a number of complex and interesting tasks which would require a not so obvious and simple approach, and solutions. In this article I will try to address some of the challenges I have faced when developing SQL Server to SQL Azure migration solutions. (more…)
My last blog (Extract-Transform-Load (ETL) Technologies – Part 1) discussed the purpose, function, and some of the inherent benefits of ETL technologies for moving data from source applications into target reporting and analytic environments. Hopefully from that discussion one can gain some general understanding of ETL; what it is, how it can be used, and why we would want to use it. Now let’s dive a bit deeper and discover who some of the key vendors are in the ETL Tools marketplace.
In 1999, when I was in my first year of university, if I wanted to check my e-mail I had to come into a lab. I used to come into the class, open browser, type address and then go out to grab some coffee. Usually when I came back I was really happy to see that at least half of the page had been loaded.
Today people are not so patient. They used to get response from the web-sites at least in a few seconds and if your application is not that fast, you have a problem. In fact, “few seconds” is a very optimistic term. Nowadays we measure response time with milliseconds. (more…)
My last blog (Column Oriented Database Technologies) discussed the differences between Row and Column oriented databases and some key players in this space. Concepts and technologies on Big Data have been discussed in previous blogs (Big Data & NoSQL Technologies & NoSQL .vs. Row .vs. Column). From these blogs one should surmise that deciding upon the best database technology (or DBMS vendor) really depends on schema complexities, how you intend to retrieve your data, and how to get it there in the first place. We’re going to dive into this next, but before we do it is imperative that we briefly examine the differences between OLTP and OLAP database designs. Then let’s leave OLTP details for a future blog as I expect most readers already know plenty about transactional database systems. Instead we’ll focus here on OLAP details and how we process Big Data using ETL technologies for data warehouse applications. (more…)