Databases

Fundamentals of Computer Science: Core Concepts for Modern Tech Computer science explains how to solve problems with computers. It blends math, logic, and practical engineering. The field changes fast, but a few ideas stay useful across many roles, from software development to data work and network design. At the core are problems and methods. Algorithms are clear steps that tell a computer what to do. Data comes in structures that help us find, sort, and access information. Programs combine these ideas with languages and tools to create useful software. ...

Databases explained for developers Databases are the backbone of most apps. They store user data, logs, and settings, and they help your code read and write information quickly. Knowing the basics helps you design better software, avoid surprises in production, and choose the right tool for the job. This guide uses plain language and simple examples so developers at any level can follow. Two big families dominate the landscape: relational databases and NoSQL databases. Relational databases store data in tables with a defined schema and powerful SQL queries. NoSQL databases use flexible formats such as documents or key-value pairs, which can be easier to scale when data shapes vary. Each approach has strengths: SQL shines with complex queries and strong consistency; NoSQL can scale horizontally and handle varied data. ...

Database Scaling: Sharding, Replication, and Caching Database scaling helps apps stay fast as traffic grows. Three common tools are sharding, replication, and caching. They address different needs: sharding distributes data, replication duplicates data for reads, and caching keeps hot data close to users. Used together, they form a practical path to higher throughput and better availability. Sharding Sharding splits data across several servers. Each shard stores part of the data. This approach increases storage capacity and lets multiple servers work in parallel. It also helps write load by spreading writes. But it adds complexity: queries that need data from more than one shard are harder, and moving data between shards requires care. ...

Databases Demystified: From SQL to NoSQL Databases come in many shapes. SQL and NoSQL are two broad families, not a competition where one always wins. The right choice depends on how you store data, how you expect to query it, and how the system will grow. Relational databases (SQL) use tables with rows and columns, a fixed schema, and strong, reliable transactions. They excel at complex queries and precise data integrity. NoSQL covers several models—document, key-value, column-family, and graph. They often offer a flexible schema, faster writes, and simpler horizontal scaling, which helps when data grows across many servers. ...

SQL Performance Tuning for High-Scale Apps High-scale applications face a constant trade-off: feature speed versus database latency. Good SQL performance comes from clear queries, steady measurement, and targeted tuning. This guide offers practical steps you can apply today and wins you can verify quickly. Start with data and plans. Track latency, throughput, and the share of slow queries. Look for patterns like scans on large tables, missing indexes, or functions on filtered columns. Use the execution plan to see where the time goes. Run EXPLAIN (ANALYZE, BUFFERS) on representative queries to learn the real costs. ...

Database Performance Tuning for Large-Scale Apps Database performance matters most where users expect instant results. In large-scale applications, small delays multiply across thousands of requests. A careful tuning plan helps you keep response times predictable without breaking features. Start with a baseline. Collect latency, throughput, and error rates. Track CPU and I/O on your database servers, and review slow queries. Use repeatable load tests to see how the system behaves as traffic grows. Clear numbers guide every tuning choice. ...

SQL vs NoSQL: When to Use Each Choosing a database type is a core part of software design. SQL and NoSQL offer different strengths. The right choice depends on data shape, how you query data, and how you plan to scale. What is SQL? SQL databases organize data into tables with a fixed schema. They use structured query language to read, filter, and join records. If you need precise results and reliable transactions, SQL is a solid option. ...

Databases 101: Structured, Semi-Structured, and Beyond Databases store information in many ways. Broadly, data lives in three zones: structured, semi-structured, and beyond. Each type fits different needs, and choosing the right one helps apps run faster and stay simple to maintain. Structured data lives in tables with a fixed schema. Relational databases like MySQL and PostgreSQL use SQL to read and write data. They shine when you need accuracy and clear rules. Example: a small shop keeps a table with columns for order_id, date, customer_id, and amount. Joins connect data from different tables, helping you report sales, inventory, and customers. Systems rely on strong consistency to keep reports trustworthy. ...

Databases Demystified: From SQL to NoSQL Databases come in many shapes. SQL and NoSQL are not enemies; they fit different tasks. SQL databases organize data in tables with rows and columns. The schema is defined in advance, and the system checks rules to keep data clean. Transactions try to keep all parts of a change correct, even in busy apps. NoSQL databases arrive with a different idea. They scale more easily across many machines and handle flexible data. They often trade strict consistency for speed and availability. This makes them useful for content storage, logs, or user sessions where fast writes matter. ...

Databases 101: From SQL to NoSQL Databases power apps and services we use every day. Two main paths guide many choices: SQL or NoSQL. SQL databases organize data in tables with rows and columns and use fixed schemas. They support powerful queries, multi-row transactions, and strong consistency. NoSQL databases come in several forms—document stores, key-value stores, column-family stores, and graph databases. They often offer flexible schemas, quick reads and writes, and easier horizontal scaling. ...