Database.Guide

Cross-Modal Retrieval Explained

June 24, 2026 by Ian

Cross-modal retrieval is an AI search technique that lets you search for data in one modality using a query from an entirely different modality. You type a description, and a search engine hands you back a matching image. Or you upload a photo, and it finds related audio clips. That’s cross-modal retrieval doing its thing.

The word “modal” just refers to a type of data, like text, images, audio, or video. “Cross-modal” means you’re working across two or more of those types. So cross-modal retrieval is when you use one type of data to search for another.

What Is AI Data Observability?

June 15, 2026 by Ian

Data pipelines break in boring ways. A field goes null, a schema changes, a job fails to run. You fix it and move on. But AI systems introduce a different kind of failure. One where everything appears to be working, the pipeline is green, the model is running, and the outputs are still wrong.

That’s the problem AI data observability is built for. It gives your team the visibility to catch data issues before they quietly corrupt model behavior, and not after someone notices the outputs are off.

JSON vs NDJSON: What’s the Difference and When Should You Use Each?

May 28, 2026 by Ian

If you’ve spent any time working with APIs or data files, you’ve probably run into JSON. It’s everywhere. But NDJSON? That one might not sound so familiar. Here’s what both formats are, how they differ, and when one makes more sense than the other.

What is Approximate Nearest Neighbor (ANN) Search?

May 20, 2026 by Ian

When you search for something using AI-powered tools, whether that’s a similar image, a related document, or a product recommendation, the system needs to find the closest matches to your query from a potentially massive dataset. Approximate Nearest Neighbor search, usually called ANN search, is the technique that makes that fast enough to be practical.

Feature Engineering Pipelines Explained

May 6, 2026 by Ian

Raw data is rarely in a form that machine learning models can use well. Feature engineering is the process of transforming that raw data into inputs that actually help a model learn. A feature engineering pipeline is the automated system that runs those transformations consistently, from the moment data comes in to the moment it reaches the model.

What Is an AI Knowledge Base?

April 29, 2026 by Ian

An AI knowledge base is a smarter way to store and retrieve information. Instead of relying on keyword search to dig through articles and documents, it lets people ask questions in plain language and get direct, relevant answers.

That’s the short version. Here’s the longer one.

What Is a Data Pipeline?

April 23, 2026 by Ian

If you’ve come across the term “data pipeline” and aren’t quite sure what it means, you’re in the right place. It sounds more technical than it is, and the main idea is actually pretty intuitive.

How to Convert a Date to a String in SQL Server

April 18, 2026 by Ian

There are a few reasons you might need to convert a date to a string in SQL Server. Maybe you need a date in a specific format for a report. Maybe you’re concatenating it with other text. Maybe an external system expects dates as strings. Whatever the reason, SQL Server gives you several ways to do it, and the right one depends on what you’re trying to achieve.

This article covers four functions: FORMAT(), CONVERT(), CAST(), and STR().

What Is a Knowledge Graph Database?

April 16, 2026 by Ian

A knowledge graph database stores information as a network of connected entities rather than rows and columns. Instead of asking “what data do we have?”, it asks “how does this data relate to everything else?” That shift in thinking is what makes it useful in situations where traditional databases start to struggle.

What Is Feature Engineering?

April 14, 2026 by Ian

Feature engineering is the process of taking raw data and transforming it into inputs that help a machine learning model learn effectively. The model doesn’t see the world the way you do. It sees numbers. Feature engineering is the work of translating your data into a numerical form that carries the right information for the problem you’re trying to solve.