database terms

What is a Slowly Changing Dimension?

January 21, 2026January 14, 2026 by Ian

In data warehousing, a slowly changing dimension (SCD) is a dimension table where the attributes change over time, but not very frequently. The term “slowly changing” refers to the fact that these changes happen occasionally (perhaps days, weeks, or months apart) rather than constantly like transactional data.

The challenge is figuring out how to handle these changes while maintaining accurate historical analysis. When a customer moves to a new state or a product gets recategorized, you need a strategy that preserves the integrity of your historical data.

What is Polyglot Persistence?

February 2, 2026January 13, 2026 by Ian

Polyglot persistence is an architectural approach where an application uses multiple different database technologies, each chosen for its specific strengths and matched to particular data storage needs. Instead of forcing all your data into one database system, you use the right database for each job. For example, a relational database for transactional data, a document store for flexible content, a cache for session data, and a graph database for relationships.

What is a CRDT?

January 10, 2026 by Ian

A CRDT (Conflict-Free Replicated Data Type) is a special type of data structure designed for distributed systems that guarantees multiple replicas of data will eventually converge to the same state without requiring coordination between nodes. Even when different users simultaneously modify the same data in different locations, CRDTs automatically resolve conflicts in a mathematically consistent way that ensures all replicas eventually agree.

The main insight behind CRDTs is that certain operations can be designed to be commutative, meaning the order in which you apply them doesn’t matter. If operation A followed by operation B produces the same result as operation B followed by operation A, you can apply updates in any order and still reach the same final state. This property eliminates the need for complex conflict resolution logic.

What is Eventual Consistency?

January 10, 2026January 8, 2026 by Ian

Eventual consistency is a consistency model used in distributed databases where data updates don’t immediately propagate to all copies, but given enough time without new updates, all copies will eventually become identical. When you write data to one location in the system, other locations might temporarily see old data, but they’ll all catch up eventually. This usually happens within milliseconds or seconds (although it can be longer during network issues or node failures).

This approach contrasts with strong consistency, where every read is guaranteed to return the most recent write immediately. With eventual consistency, the system prioritizes availability and performance over immediate accuracy. You’re accepting that different parts of your database might temporarily disagree about the current state of the data in exchange for faster operations and better fault tolerance.

Understanding Locks in SQL Server

January 17, 2026January 7, 2026 by Ian

If you’ve ever wondered why your database queries sometimes seem to wait around doing nothing, or why two users can’t update the same record at the exact same moment, you’re dealing with locks. In SQL Server, locks are the fundamental mechanism that keeps your data consistent and prevents the chaos that would ensue if everyone could modify everything simultaneously.

What is a Columnstore Index?

January 6, 2026 by Ian

A columnstore index is a type of database index that stores data by column rather than by row. Traditional indexes (and tables) store data row-by-row, where all the values for a single record are kept together. Columnstore indexes flip this around, storing all values from a single column together instead.

This might seem like a small difference, but it fundamentally changes how the database reads and processes data. Columnstore indexes are designed for analytical queries that scan large amounts of data, performing aggregations, calculations, and filtering across millions or billions of rows.

What is Vertical Scaling?

January 4, 2026 by Ian

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?

January 8, 2026January 3, 2026 by Ian

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.

What is Database Sharding?

January 8, 2026January 1, 2026 by Ian

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.

What is a Cloud Database?

January 26, 2026December 30, 2025 by Ian

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.