Technical writing

Build an application in Kotlin that utilizes full-text search in a database containing thousands of Airbnb listings to find the perfect accommodation.

Sharding as a horizontal scaling strategy, understanding a sharded cluster architecture, shards, config servers, mongos, and distributing data.

What's new in version 8.0, general changes, Queryable Encryption, Express query stages, query shape and query settings, compatibility and more.

Have you ever imagined taking a photo of yourself, comparing it against a database full of celebrities, and instantly finding out who you look most alike?

Prerequisites, one-to-many relationships, avoiding embedded inside books, and moving reviews to a separate collection.

How MongoDB fits in, prerequisites, tag your Atlas cluster, project overview, setting up the project, configure Hibernate, the Book entity.

One search might not be enough. Merging the best of both worlds: prerequisites, project setup, full-text search, implementing the full-text index.

Adding filters from story to code, post-filter in MovieService, pre-filter approach, refining the search with extra filters and applying toCriteria.

The magic behind vector search, prerequisites, set up embeddings, work with embeddings, and MongoDB Atlas Vector Search.

Why Queryable Encryption, a quick look at Spring MongoDB integration, defining encrypted fields, configuration, and dependencies.

A realistic aggregation scenario, writing the test, testing on M0, the hidden risk, and taking it to production with the same queries on different environments.

One of the discussions that always leaves me with both doubts and excitement is the one about hexagonal architecture, diving deeper into modular design.

Finding exactly the data we need isn't always simple. Learn how to filter, group, and perform calculations using MongoDB's Aggregation Framework.

Learn how to optimize a Spring Data MongoDB application through indexes and read preferences. This third and final part of the series covers single field, compound, unique, and TTL/partial indexes, as well as ReadPreference strategies.

Explore Spring Data's capabilities by creating advanced queries with MongoRepository and MongoTemplate. This second part of the series covers derived queries, @Query, @Update, @Aggregation, pagination, and bulk operations.

Learn how to integrate MongoDB with Spring Data in a simple and easy way. This first part of the series covers getting started with Spring Data, modeling your data, and using MongoRepository to perform basic CRUD operations.

Learn how to seamlessly integrate Java with MongoDB Queryable Encryption in a fully automated way. This process allows you to leverage the advanced encryption features of MongoDB, ensuring that your data remains protected even during complex queries, without the need for manual encryption or decryption steps

Learn how to integrate Vector Search into your Kotlin with Ktor application using MongoDB.

Set up a Ktor project, implement CRUD operations, define API route endpoints, and run the application. Understand Kotlin's capabilities in API development.

Explore Query With Natural Language, a revolutionary feature in MongoDB Compass that lets you write queries using plain English.

Key facets of MongoDB Replication, including high availability and data redundancy, complemented by an accessible video walkthrough.

Optimizing MongoDB queries through the strategic use of indexes and analyzing their results using the Explain Plan feature in MongoDB Compass.

MongoDB's Relational Migrator feature demonstrated with a sample showing how to create and migrate a database from PostgreSQL to MongoDB.

Importing a JSON file into a MongoDB Atlas cluster using MongoDB tools and building powerful charts and visualizations on top of that data.

How to create a Grafana instance, access it, and generate graphs using data from a PostgreSQL database running in Docker.

An exploration of the Observer Pattern, a design pattern commonly used in software development, with a simple and practical Kotlin implementation.

How to deploy a Quarkus application to Elastic Beanstalk and a closer look at some of the key benefits and best practices for using these two technologies together.

The final part of building our daily-quotes application with Quarkus, Angular, and Keycloak authentication.

Continuing the development of our daily-quotes application with Quarkus, Angular and Keycloak.

Delving into the authentication mechanism of Keycloak and the creation of a daily-quotes application using Angular + Quarkus, divided into three parts.

Searching and sorting are fundamental concepts in programming. Learn how to implement a binary search algorithm that traverses a list or array in Java.

Trees are one of the most fundamental data structures for storing data. A binary tree is defined as a data structure organized in a binary way, where each node has at most two children.