If you’ve spent any time working with SQL databases, you’ve probably heard of ACID properties. These are the strict guarantees that traditional relational databases provide to keep your data consistent and reliable. But when it comes to distributed systems and NoSQL databases, it’s less about ACID and more about BASE.
Ian
What is a Database Transaction?
A database transaction is a sequence of operations performed as a single logical unit of work. The key idea is that all the operations in a transaction either complete successfully together or fail completely. There’s no in-between. This ensures the database remains consistent even if something goes wrong, like a power outage or a failed query.
In simpler terms, a transaction lets you group multiple SQL statements into one reliable operation. If everything runs smoothly, you commit the changes. If not, you roll back the entire transaction, leaving the database exactly as it was before it started.
How to Prevent Overflow Errors When Aggregating Data in SQL Server
When working with aggregate functions in SQL Server, it’s easy to overlook that certain datatypes have strict limits. If you’re summing values in large tables (or even just summing very large numbers), you might run into an arithmetic overflow error. This happens when the result of an aggregate exceeds the maximum value the datatype can hold.
Understanding how this works and how to prevent errors will help you write reliable queries.
How to Use Window Functions to Find Duplicates in SQL Server
When you’re working with real-world data, duplicates can sometimes sneak in more often than we’d like. Maybe an import process didn’t filter things properly, or users managed to submit the same information twice. Whatever the reason, finding and handling duplicates is a common task.
A neat way to tackle this problem in SQL Server is by using window functions. Specifically, we can use ROW_NUMBER() or RANK() to find duplicate rows in a table. These functions let you assign a sequence number to rows within a group, which makes it easy to spot duplicates.
Convert UTC to Local Time in SQL Server
When dealing with applications that span multiple time zones, you’ll often want to store timestamps in UTC. That’s usually the best practice – it avoids confusion and ensures consistency. But sooner or later you’ll need to show users dates and times in their own local time zones. There are a few ways to handle this in SQL Server.
How to Choose Appropriate NUMERIC Precision to Avoid Overflow in SQL Server
When working with SQL Server, numeric precision can become a silent troublemaker if you’re not careful. Overflow errors happen when a number exceeds the storage capacity of the column data type. Unlike other errors that are easy to catch in testing, numeric overflow often shows up unexpectedly in production, which can be costly. Understanding how to pick the right precision and scale for your NUMERIC or DECIMAL columns can save you headaches down the road.
Hard vs Soft Dependency in SQL
When you’re building or maintaining a relational database, objects rarely live in isolation. Tables support views, views feed reports, procedures call other procedures, and constraints tie data together. These relationships are called dependencies, and they can be hard or soft.
The difference boils down to how strictly the database enforces the relationship.
How to Handle Server vs Session Time Zone Settings in SQL Server
Working with dates and times in SQL Server can get tricky, especially once you add time zones into the mix. One common point of confusion is the difference between the server’s time zone and the session’s time zone. If you’re not careful, you can end up with inconsistent data or timestamps that don’t line up with what your users expect.
Let’s look at how SQL Server treats time zones and how you can handle server versus session time zone differences cleanly.
Avoiding “Columns Mismatch” Errors in INSERT Statements
A “columns mismatch” error in SQL usually happens when the number of values you’re trying to insert doesn’t line up with the number of columns in the table. It’s not a complicated issue, but it can be an easy one to overlook, especially when working with tables that evolve over time or when you skip specifying column names in your INSERT statements.
Understanding why the error occurs makes it simple to avoid, and a few small habits can help keep your SQL inserts clean and reliable.
When to Use TRY_CONVERT() vs CONVERT() in SQL Server
Both CONVERT() and TRY_CONVERT() in SQL Server are used to convert data types, but they behave quite differently when something goes wrong. Understanding that difference can save you a lot of debugging time, especially when dealing with messy or unpredictable data.
Let’s look at when you should use each, and walk through an example that you can run yourself.