Beyond Keywords: Hybrid Search With Atlas and Vector Search (Part 3)
Bringing together semantic vectors and exact keyword matching with $rankFusionIf you’ve been following along this series, you already know …
Databases
The Cost of Not Knowing MongoDB - Part 3: (appV6R0 to appV6R4)
Welcome to the third and final part of the series "The Cost of Not Knowing MongoDB." Building upon the foundational optimizations explored …
Modeling Relationships With Hibernate ORM and MongoDB
In the previous article—Getting Started With Hibernate ORM and MongoDB—we learned how to configure Hibernate to work with MongoDB, create an …
Getting Started With Hibernate ORM and MongoDB
For years, Hibernate ORM has been one of the most popular frameworks in the Java ecosystem. It was built to simplify data persistence by …
The Pitfall of Increasing Read Capacity by Reading From Secondary Nodes in a MongoDB Replica Set
Imagine we are responsible for managing the MongoDB cluster that supports our country's national financial payment system, similar to Pix in …
How MongoDB Decides What to Forget?
Inside MongoDB’s storage engine, WiredTiger, nothing happens by accident. Every page in memory exists under policy — governed, measured, and …
Beyond Keywords: Optimizing Vector Search with Filters and Caching (Part 2)
Welcome back! If you landed here without reading Part 1: Beyond Keywords: Implementing Semantic Search in Java With Spring Data, I recommend …
The Cost of Not Knowing MongoDB - Part 2
This is the second part of the series “The Cost of Not Knowing MongoDB,” where we go through many ways we can model our MongoDB schemas for …
Beyond Keywords: Implementing Semantic Search in Java With Spring Data (Part 1)
Have you ever tried to search for something such as a product, a song, or a movie but couldn’t quite remember its exact name? Maybe you …
The Cost of Not Knowing MongoDB (Part 1)
The primary focus of this series is to show how much performance you can gain, and as a consequence, the cost you can save when using …