SQL Server’s Query Store accumulates query execution history, plans, and runtime statistics over time. Eventually you may need to remove this data to free up space, start fresh after troubleshooting, or clear out information that’s no longer relevant. Fortunately, you can clear Query Store data without disabling the feature entirely.
Ian
What is Vertical Scaling?
Vertical scaling is the practice of increasing the capacity of a single server by adding more resources to it. For example more CPU power, RAM, storage, or faster hardware. Instead of adding more machines to handle increased load, you make your existing machine more powerful.
In database contexts, vertical scaling means upgrading your database server to more powerful hardware so it can handle more queries, store more data, and process transactions faster. It’s the most straightforward way to improve database performance.
What is Horizontal Scaling?
Horizontal scaling is the practice of adding more servers or machines to your system to handle increased load, rather than making individual servers more powerful. Instead of upgrading one server with more CPU and RAM, you add additional servers and distribute the work across all of them.
How to Force a Query Execution Plan in SQL Server
When the optimizer consistently chooses a poor execution plan for a query, you can force SQL Server to use a specific better-performing plan from Query Store. This can provide immediate relief while you investigate and fix the root cause of the poor plan choice.
What is Database Sharding?
Database sharding is a technique for splitting a large database into smaller, more manageable pieces called shards. Each shard contains a subset of the total data and operates as an independent database. Together, all the shards hold the complete dataset, but queries are distributed across them to improve performance and scalability.
List of Query Store Configuration Options in SQL Server
SQL Server’s Query Store provides a handy way to track query performance over time, making it easier to troubleshoot issues and optimize workloads. To get the most out of it, it helps to understand the various configuration options that control how it collects, stores, and manages data.
What is a Cloud Database?
A cloud database is a database that runs on cloud computing platforms rather than on local servers or personal computers. Instead of installing and managing database software on your own hardware, you access the database over the internet through a cloud provider like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform.
Basic Database Terms for Beginners
If you’re just getting into databases, the terminology can sometimes feel overwhelming. Between acronyms like SQL and CRUD, technical jargon like normalization and schema, and concepts that sound similar but mean different things, it’s easy to get lost before you even start.
Let’s break down the essential concepts you need to know to actually understand what people are talking about.
What is a Dimension Table?
In data warehousing and analytics systems, dimension tables provide context for the measurements stored in fact tables. While fact tables contain the numbers you want to analyze, dimension tables tell you what those numbers mean. This could be things like who was involved, what product it was, when it happened, where it occurred, etc.
Basically, dimension tables are the “descriptive” side of dimensional modeling, containing the attributes and characteristics that let you filter, group, and label your data in meaningful ways.
What is a Fact Table?
In data warehousing and analytics databases, a fact table is where you store the actual measurements and metrics of your business. It’s the table that contains the numbers you want to analyze. This could include things like sales amounts, quantities, counts, durations, or any other quantifiable data points.
Fact tables are the foundation of dimensional modeling, the approach most commonly used for organizing data in data warehouses and business intelligence systems.