MongoDB makes it really easy to work with location data (sometimes called Geo Data) by simplifying how to store this type of data and streamlining how you query for it so you can easily create “find nearby” queries, or plot …
-
Agents Meet Databases: The Future of Agentic Architectures
Table of Contents A Quick Overview of AgentsPath 1: Standardized Integration with MCP serversPath 2: Custom Integrations for Control and FlexibilityAccuracy, Security, and Performance ConsiderationsAccuracy: Ensure Reliable Query GenerationSecurity: Maintain Protection and GuardrailsPerformance: Manage Unpredictable Agentic WorkloadsThe Agentic Future Depends …
-
Introduction to Data-Driven Testing with Java and MongoDB
Table of Contents PrerequisitesStep 1: Create the entitiesExplanation of annotations:Step 2: Create a database containerStep 3: Generate our first DDTConclusion As applications expand, the complexity of the rules they enforce also increases. In many systems, these rules are embedded within …
-
Power your AI application with Vector Search
Most major database vendors, like MongoDB , are adding vector search capabilities to their products. It’s becoming a standard feature as demand for AI-powered applications grows. 🕒 Reading time: 3-4 min 🧠 What is vector search needed for? MongoDB Vector …
-
From Zero to Vector Hero – Locally!
In the previous issue, I explained how to run a local MongoDB Atlas cluster using Atlas CLI – no cloud account required. If you missed it, read it here 👉 Run an Atlas cluster locally in minutes. Now let’s see …
-
Best Practices for Deploying MongoDB in Kubernetes
Table of Contents 1. Use the MongoDB Kubernetes Operator2. StatefulSets and persistent volumes: Running MongoDB the right wayExample: Recommended multiple volume configuration3. Set CPU and memory resources for MongoDB and the OperatorMongoDB Kubernetes Operator: Plan for initial spikesMongoDB replica set …
-
MongoDB Schemas in Java
Table of Contents Why MongoDB and Java are such good friendsThe missing schema of loosely typed systems Bringing schema back Example: Spring Boot sea temperature service Sea temperatures Weather reports Schemas Data access Creating our API Why not Spring Data? Java benefits Schema in one place Database pollution API input pollution Compile-time and …
-
Building REST APIs in Java with Spring Boot
Table of Contents How can Spring help?PrerequisitesCreating our appConnecting our databaseOur Book modelBook repositoryOur REST controllerCreateReadUpdateDeleteAdding DTOs and validationBookRequestBookResponseUpdating the controllerTesting the APIRun the APICreateReadUpdateDeleteConclusion REST has become the default choice for building web services, and for good reason. It’s …
-
MongoDB Aggregations: Organizing Recipes by Meal Type with $group
Table of Contents Why Use $group for Organizing Recipes?Setting Up the DataUsing $group to Organize Recipes by TypeStep 1: Grouping Recipes by TypeStep 2: Including Recipe Details in Each GroupGrouping Recipes by TagsStep 1: Using $unwind to Break Down TagsAdvanced …
-
Queryable Encryption With Spring Data MongoDB: How to Query Encrypted Fields
Table of Contents Why Queryable Encryption?A quick look at Spring Data MongoDBUse case: HR system with encrypted fieldsSetting up the projectConfiguring dependencies and propertiesAdding mongodb-cryptApplication.yml configurationAccessing properties in the codeBuilding the application layersThe domain modelThe repositoryThe serviceThe controllerSetting up encryptionConfiguring …
-
What happens when a Primary fails in a MongoDB replica set? Automatic failovers?
In distributed systems, high availability is not a luxury—it’s a necessity. And one of the very important parts of that is automatic failovers. What are automatic failovers and how do they work? Let’s see today! These concepts are actually similar …
