This article introduces and compares major database categories—including relational, key‑value, document, columnar, graph, and time‑series databases—explaining their structures, typical use cases, and advantages, helping readers understand when to choose each type for various applications.
The February 2022 DB‑Engines ranking shows Snowflake’s rapid rise, a sharp decline for Oracle, MySQL and Microsoft SQL Server, stable positions for Elasticsearch, and detailed score trends across relational, key‑value, document, time‑series and graph databases, highlighting five popularity metrics used for the assessment.
This article provides a concise tutorial on Elasticsearch 7.x, explaining what documents and indices are, how unique IDs and metadata work, and demonstrating key REST API commands for managing and querying data in a search‑engine context.
This article explains what NoSQL databases are, introduces the CAP theorem that underlies their design trade‑offs, outlines typical application scenarios, discusses their limitations, classifies the main NoSQL families, and reviews four widely used systems—Redis, HBase, Cassandra, and MongoDB.
This article explains how Elasticsearch stores JSON documents, indexes them, and uses RESTful PUT, GET, DELETE, and search APIs to perform create, read, update, and delete operations, illustrating each step with concrete employee examples and query syntax.
This article explains the limitations of traditional relational databases, introduces the emergence of NoSQL, categorizes its four main types—key‑value, document‑oriented, column‑family, and graph—detailing popular products, typical use cases, and scenarios where each is unsuitable.
An overview of NoSQL database types—including key‑value stores like Redis, column‑oriented systems such as BigTable and HBase, and document databases like MongoDB—covers their architectures, strengths, typical use cases, and key factors to consider when selecting a NoSQL solution for web applications.
