As a rule, impersonal information is stored in a public cloud, and the personalized part – in a private cloud. The question thus arises – how to combine both parts to return a single result at a user’s request? Suppose there is a table of customers divided vertically. The depersonalized columns were included in the table located in Windows Azure SQL Database, and columns with sensitive information (e.g., full name) remained in the local SQL Server. Both tables must be linked by the CustomerID key. Because they are located in different databases on different servers, the JOIN statement will not work. As a possible solution, we have considered the scenario, when the linkage was implemented on the local SQL Server. It served as a kind of entry point for the applications, and the cloud-based SQL Server was set up on it as a linked server. In this article, we will consider the case when both, the local and cloud servers, are equal in terms of the application, and the data merging occurs directly in it, i.e. at the business logic level.
A hybrid cloud is a fairly attractive model when implementing cloud computing in enterprise information systems since this approach combines the advantages of public and private clouds. On the one hand, it is possible to flexibly attract external resources when needed and reduce infrastructure costs. On the other hand, full control over data and applications that the enterprise does not want to outsource remains. However, in such a scenario, we inevitably face the task of integrating data from various sources. Suppose there is a table with customers, which is vertically divided into two parts. The depersonalized part was allocated in a public cloud, and the information personalizing the customers remained in a local database. For holistic processing inside the application, you need to combine both parts by CustomerID. There are various ways to do this. Conventionally, they can be divided into two large categories: data aggregation at the on-premise database server level which, in this case, will be a single sign on for accessing local and remote data, and data aggregation within the business logic. This article will consider the first approach.
Autumn of 2016 was full of events from Microsoft dedicated to analytics. In practice, the company began aggressive promotion of its predictive analytics and BI platform in the cloud. Finally, it has happened – Microsoft has released the preview of Azure SSAS Tabular. In fact, the company has transferred SSAS Tabular to the cloud. Therefore, SQL Server Analysis Enterprise Edition in cloud supports DirectQuery, partitions, row-level security, bi-directional relationships, and has compatibility level 1200.
In this post, I’d like to take a brief look at the Query Performance Insight — SQL Azure tool which will help you to identify the most expensive queries in your database.
Query Performance Insights was announced in early October 2015. To understand what it is, let’s think about how do you usually learn that the database performance got down? Probably, you are receiving emails from your clients or it takes an hour to create a weekly report instead of a several minutes, or maybe, your application starts throwing exceptions. (more…)
Active Directory traditionally used to manage elements of a domain-based network. But companies increasingly implement various cloud services that require its own user accounts. A tool for creating and managing user accounts, that are used by different Microsoft cloud services, which a company acquires, is Azure Active Directory. (more…)