In the series on the SQL Server FILESTREAM feature, we have explored the various aspects of FILESTREAM including its overview, internal architecture, database creation etc. In my last article [put the name of the article and a link], we explored the backup for the FILESTREAM enabled database. We can take Full backup as well as filegroup level backup in the FILESTREAM database.
The SQL Server FILESTREAM feature in SQL Server allows storing the large documents files directly into the file systems. In my previous articles, we explored the concepts of FILESTREAM feature in SQL Server. We also learned the folder structures, metadata information and the process of garbage collection. In this article, we are going to learn about the backup and restores in SQL Server.
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SQL Server FILESTREAM allows storing the Varbinary (Max) objects in the file system instead of placing them inside the database. In the previous article – FILESTREAM in SQL Server, we took an overview of the FILESTREAM feature in SQL Server and process to enable this feature in SQL Server Instance.
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This article will discuss SQL Server FILESTREAM including installation, configuration, enabling and general considerations.
A SQL index is used to retrieve data from a database very fast. Indexing a table or view is, without a doubt, one of the best ways to improve the performance of queries and applications.
A SQL index is a quick lookup table for finding records users need to search frequently. An index is small, fast, and optimized for quick lookups. It is very useful for connecting the relational tables and searching large tables.
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In addition to specifically addressing database normalization in SQL Server, this article will also address the following questions:
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SQL Server 2017 introduced Graph database features where we can represent the complex relationship or hierarchical data. We can explore the following articles to get familiar with the concept of the Graph database.
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In the other article in this series: Deploy SQL Server for failover clustering with Cluster Shared Volumes – part 1 we have seen what a cluster shared volume is and what are the advantages and other considerations to keep in mind when deploying CSVs for SQL Server workloads. In this article, I will walk though actual installation of a failover cluster Instance leveraging CSVs.
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Deleting or changing objects may affect other database objects like views or procedures that depends on them and in certain instances, can “break” the depending object. An example can be that if a View queries a table and the name of that table changes. The View will no longer function.
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Microsoft SQL Server provides us with a wide variety of solutions to architect High availability (HA) and Disaster Recovery (DR) solutions for mission-critical workloads. In this article, let’s just focus on HA, specifically Failover Clustering. Failover clustering is probably the most mature, robust and stable high availability solution which Windows Server Operating system offers. It’s been there around for few decades now and did evolve over time along with SQL Server. In this article Let’s see a hidden feature of windows server failover cluster which helps in making our already highly available SQL Server Failover clustered instances even more highly available. The new feature which we are going to talk about is Cluster Shared Volumes, AKA CSVs. Considering windows server 2019 is around the corner, I say CSVs are not a new concept in clustering, it’s been there for almost a decade now. Microsoft introduced CSVs in windows server 2008R2, but at that time SQL Server was not supported on CSVs. Well, CSVs were originally designed for Hyper-V workloads and later on enhanced for File servers and eventually landed into SQL Server beginning version 2014.
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In SQL Server, both the SEQUENCE object and IDENTITY property are used to generate a sequence of numeric values in an ascending order. However, there are several differences between the IDENTITY property and SEQUENCE object. In this article, we will look at these differences.
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SQL Server 2017 is considered a major release in the history of the SQL Server life cycle for various reasons. From my personal point of view, SQL Server 2017 is indeed an interesting release. After writing lot about it and testing various features of SQL Server 2017, I’d like to walk you through some of its interesting features.
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The real-life requirement
Disclaimer: I assume dear Reader, that you are more than familiar with the general concept of partitioning and star schema modeling. The intended audience is people who used to be called BI developers in the past (with a good amount of experience), but they have all sorts of different titles nowadays that I can’t keep up with… I won’t provide a full Visual Studio solution that you can download and just run without any changes or configuration, but I will give you code can be used after parameterizing according to your own environment.
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Intended audience
This document is intended for application developers and database administrators who are willing to get an overview of comm concurrency problems to which transaction isolation levels respond in the particular case of Microsoft SQL Server.
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We’ve recently had production failures because our developers changed an important reference. In this case, we had a view which several procedures and views referenced. A developer made a change to the referenced view by removing columns, which caused several procedures and a view that referenced it to fail. We’re considering whether we should stop this practice, or if there are other ways we can prevent changes to an object that’s being referenced by other objects (in our case, a view).
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In relational database systems, objects have different types of relationships with each other. Apart from table relationships (such as one to one, one to many and many to many), objects such as stored procedures, views, custom functions also have dependencies on other objects. It is important to understand object dependencies, particularly if you want to update an object that depends upon other objects.
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One of the best ways to optimize performance in a database is to design it right the first time! Making design and architecture decisions based on facts and best practices will reduce technical debt and the number of fixes that you need to implement in the future.
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SQL server furnishes us with the geometry and geography SQL data types for conserving spatial data, which allows us to render graphical data. To be more specific, it is beneficial for creating, analyzing, comparing and retrieving spatial data.
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In SQL Server, when talking about table partitions, basically, SQL Server doesn’t directly support hash partitions. It has an own logically built function using persisted computed columns for distributing data across horizontal partitions called a Hash partition.
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Earlier this year, I published several articles on SQLShack with an aim of demonstrating tools available for visualising SQL Server 2017 graph databases. I was so caught up in the excitement of having SQL Server finally support graph databases that I forgot that some people still do not have a good grasp of how graph databases work let alone consider replacing their relational databases models in favour of graph. Although there are several ways that one can go about explaining the usefulness of graph databases over its relational counterpart, I have opted to focus on the benefits and strengths of graph databases by demonstrating the differences in which graph and relational databases deal with hierarchical datasets.
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This article explains data security for accessing sensitive data and restricts access in application using SQL Views and stored procedures.
We recently faced a leak of information for one of our employees that involved data which caused a conflict within our company, even if it was not personally identifiable information (PII data). When we investigated the issue, we uncovered that we need to organize data access for our teams and review who has access to what information. As of right now, all our users either have access to all tables directly or a subset of all our tables. What are some practices we can use in SQL Server to avoid giving direct table access to our users? Read more »
Foreign key constraints are a powerful mechanism for preserving referential integrity in a database. They can also represent a challenge when doing bulk table loads, since you need to find a “base” table to start with – that is, a table that has no foreign key constraints defined. Let’s label tables like this as level 0, or ground level if you like. Once that is loaded, you can begin to load other tables that have foreign key references to the base table. We can label those tables level 1, and so on. If you start with table data that already has referentially integrity and load tables by their level numbers — level 0, level 1, level 2 and so on – the load should proceed without problems. Let’s look at a simple example:
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We receive many database alerts with many of the alerts logging some of these same alerts or information to files or tables. What we’ve found over time is that the logging is now costing us quite a bit of resource. Our logging server (where both files and table logging are stored) has had a few outages related to conflicts from messages for other servers. We’ve considered scaling the alerting by environment type, but we’ve also considered that we may be logging too much information about our databases. In addition, since we receive so many alerts each day, it’s impossible for us to resolve them and assist with other issues that arise. What are some techniques that we can use to help us with the issue of too much logging information and too many alerts? Read more »
In this article, we are going to see how to add a new disk to an existing SQL Server failover clustered instance (which I will be referring as FCI from now on). Let’s assume a scenario where you have an existing FCI with dedicated data and log drives and you want to add a new disk (Let’s say you have a new requirement to store your backups locally).
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GUID is a 16 byte binary SQL Server data type that is globally unique across tables, databases, and servers. The term GUID stands for Globally Unique Identifier and it is used interchangeably with UNIQUEIDENTIFIER.
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