Tech Fundamentals

SQL vs NoSQL Databases: When to Use Each SQL databases store data in tables with a fixed schema and use a structured query language for joins and reports. NoSQL systems cover document stores, key-value stores, wide-column stores, and graphs. Both kinds help apps store data, but they differ in structure, scale, and how you work with data. The right choice depends on data shape, access patterns, and growth plans. When to use SQL Choose SQL when data is structured, relationships matter, and you need reliable transactions. Common scenarios include customer orders, financial records, and inventory. Benefits include strong ACID guarantees, powerful ad hoc queries, and a mature ecosystem with many tools and integrations. ...

Inside Operating Systems: How Scheduling, Memory, and I/O Work Together Computers run many tasks at once. The operating system coordinates three main resources: CPU time, memory, and I/O devices. When these parts work well together, apps feel fast and smooth. If one part slows down, the whole system can feel sluggish. The collaboration among scheduling, memory management, and I/O control is the secret behind responsive software. Scheduling the CPU The CPU scheduler decides which task runs next. The ready queue holds processes and threads waiting for CPU time. The kernel uses rules like time slices and priorities to switch tasks without freezing. This gives many apps a fair share of CPU time. The goal is quick replies and steady progress. ...

APIs and Middleware: Building Bridges Between Applications APIs and middleware are the quiet helpers of modern software. They let different apps talk to each other and share data. An API is a set of rules that another program can follow to access features or information. Middleware sits between services, handling tasks like security, routing, data transformation, and message queues. Together, they build reliable bridges rather than fragile ties. What middleware does in practice ...

Databases 101: From Storage to Query Optimization Databases are more than files on a disk. They organize data so apps can read and write quickly, safely, and predictably. This guide walks from how data is stored to how a database chooses a fast plan to answer a query. Storage and data models. In a relational system, data sits in tables with rows and columns. The storage engine decides how these rows are kept on disk—row-oriented pages for fast single-row access, or columnar blocks for analytics. Other models, like key-value or document stores, use different layouts but still rely on fast lookups. ...

Databases 101 From Relational to NoSQL Databases are the backbone of software, turning raw data into useful information. They come in many forms, but they mainly fall into two broad families: relational databases and NoSQL databases. Relational systems use tables with a fixed schema and rely on SQL for queries. NoSQL covers several data models that adapt to varied needs, often offering flexible schemas and different consistency rules that fit fast growth and changing data patterns. ...

Databases 101: Models, Queries, and Performance Databases store data for apps. They organize information so programs can read and update it quickly. There are many models, and each has its own strengths. This article covers three core ideas: data models, how queries fetch information, and what affects speed and reliability. The goal is to help you choose the right approach for common tasks and to read performance hints without getting overwhelmed. ...

Databases for Scale: Sharding, Replication, and Performance When apps grow, data workloads change. You need a plan that balances capacity, reliability, and speed. The three pillars most teams use are sharding, replication, and performance tuning. Each has clear goals and trade-offs, and they often work best together. Sharding distributes data across multiple database instances. This reduces hot spots and lets queries run in parallel. You might shard by customer, region, or a user ID range. Common strategies include hash-based sharding, range-based sharding, and directory-based sharding which combines ideas. The benefit is more throughput, but cross-shard queries become harder and rebalancing data can require downtime or careful orchestration. A practical approach is to start with a simple shard key and keep migrations small and reversible. ...

Operating System Fundamentals Explained for Developers An operating system (OS) sits between your program and the computer hardware. It manages memory, handles input and output, runs multiple tasks, and keeps apps safe from each other. For developers, knowing the basics helps you write better code, debug faster, and choose the right abstractions. What an OS does matters to everyday coding. It creates a clean interface for apps, schedules work so the system stays responsive, and provides a set of building blocks—processes, threads, files, and networking—that you rely on without worrying about the low-level details. ...

SQL Versus NoSQL: Choosing the Right Database Choosing a database is a core part of building software. SQL databases are relational systems. They use tables with defined schemas, and they enforce ACID transactions for consistency. NoSQL includes document stores, key-value stores, wide-column databases, and graph databases. They are usually schema-flexible and designed to scale out across many servers. This mix means you can pick a store that fits your data and your goals. ...