0 views collected around this technical thread.
This article explores how modern data technologies—from relational databases and NoSQL to vector databases and AI‑driven retrieval—address the 4V challenges of volume, velocity, variety, and value, enabling polyglot persistence, semantic embeddings, and retrieval‑augmented generation for next‑generation applications.
This article provides an in‑depth overview of nine major database categories—including relational, key‑value, columnar, document, graph, time‑series, and vector databases—detailing their strengths, weaknesses, best practices, and typical application scenarios, and explains how polyglot persistence combines multiple databases for optimal performance and scalability.
This article provides an in‑depth survey of nine database categories—including relational, key‑value, columnar, document, graph, time‑series, and vector databases—detailing their architectures, advantages, disadvantages, best‑practice recommendations, typical use cases, and how they can be combined in polyglot persistence solutions.
This article explains how to design data architecture for microservice systems, covering the advantages of microservices, decoupling principles, lightweight APIs, DevOps integration, database per service versus shared databases, polyglot persistence, and why MongoDB is a suitable choice for scalable, dynamic, and sharded data storage.
This article explains microservice fundamentals, outlines their advantages, and provides detailed guidance on data design, database selection, and scaling techniques—including decoupling, lightweight APIs, DevOps CI/CD, polyglot persistence, and sharding—to help architects build robust, flexible microservice systems.
This article explains microservice fundamentals, their advantages, technical characteristics, and detailed data‑design considerations, comparing shared versus per‑service databases, polyglot persistence versus multi‑model databases, and demonstrates why MongoDB is a strong fit for scalable, resilient microservice architectures.
This article explains microservice fundamentals, their advantages, technical characteristics, and provides a comprehensive guide to data design in microservice architectures, covering decoupling, lightweight APIs, continuous delivery, database per service versus shared databases, polyglot persistence, scaling strategies, and why MongoDB is a suitable choice.
The article explains how microservices must own their own domain data and logic, contrasts this with monolithic shared‑database approaches, discusses the relationship to Domain‑Driven Design bounded contexts, and highlights challenges such as distributed transactions, eventual consistency, and polyglot persistence.
This article explains how to design data architecture for microservice systems, covering microservice fundamentals, advantages, decoupling, lightweight APIs, continuous delivery, database per service versus shared databases, polyglot persistence, scaling dimensions, sharding strategies, and why MongoDB is a suitable choice.