Enterprise data platforms face common questions—why add a data warehouse when MySQL or Oracle exist, why introduce a data lake after a warehouse, and what problems NoSQL, ClickHouse, or Doris solve—this article breaks down six storage technologies, their core use‑cases, and how to choose among them.
This article demystifies databases by contrasting them with Excel, explains core concepts such as tables, rows, columns, primary and foreign keys, compares relational and NoSQL systems, introduces SQL CRUD operations, ACID properties, and provides a quick MySQL hands‑on guide, helping readers decide when to adopt a database.
This lesson walks through relational database normalization using a messy enrollment table, showing how to derive functional dependencies, identify candidate keys, detect partial, transitive and BCNF violations, and systematically decompose the schema into student, major, course, teacher and enrollment tables while ensuring lossless joins and dependency preservation.
The article contrasts Elasticsearch’s search‑oriented design—using inverted indexes, near‑real‑time BASE consistency, schema‑free JSON documents, and horizontal scaling—with relational databases’ precise row‑based storage, ACID guarantees, strict schemas, B+‑tree indexes, and vertical scaling, showing how they complement rather than compete.
As data volumes surge, the article compares six mainstream storage technologies—relational databases, data warehouses, NoSQL databases, search storage, object storage, and data lakes—explaining their core principles, ideal use cases, and trade‑offs to help you select the most suitable solution for your workload.
This article uses everyday analogies—herbal shops, libraries, and refrigerators—to demystify databases, covering relational tables, primary/secondary keys, foreign keys, DBMS, and SQL in a clear, beginner‑friendly way.
This article introduces core relational database concepts, covering tables, data models and ER diagrams, the fundamentals of SQL, and the first three normal forms, providing clear explanations and examples to build a solid foundation for further database study.
This article explains eight key reasons why SQL and relational database systems remain the dominant data management solution half a century after their invention, covering performance, maturity, community, simplicity, popularity, open‑source options, powerful query capabilities, and their continued relevance alongside newer technologies.
This article traces PostgreSQL's origins from the 1980s INGRES project, compares navigation and relational databases, outlines its evolution through Postgres95 to PostgreSQL, and highlights ten modern features that make it a powerful, scalable, and secure choice for developers today.
This guide introduces Lealone, a Java open‑source high‑performance relational database for OLTP, outlines its key features, provides step‑by‑step instructions for downloading, starting, and using the server and client, shows JDBC CRUD examples, GUI client setup, and links to the author's technical blogs and source notes.
This article provides a comprehensive analysis of the Chinese database industry, covering global trends such as the dominance of relational databases and the rise of NoSQL, the impact of cloud vendors and open‑source, domestic market opportunities, classifications of database types, and profiles of leading Chinese vendors, highlighting how big‑data and AI are reshaping demand and creating growth prospects for home‑grown solutions.
This article provides a comprehensive overview of Oracle's database products, explaining why they matter, detailing the physical and logical storage structures, instance processes and memory areas, and tracing the evolution from early versions through RAC, multitenancy, and the latest 18c features.
This whitepaper explains the definition and history of in‑memory databases, discusses their performance advantages and persistence challenges, outlines the technology’s maturity and bottlenecks, classifies key products, and provides technical and non‑technical criteria for selecting the most suitable solution for high‑concurrency, low‑latency workloads.
The 2020 IDC report shows Alibaba Cloud leading China’s relational database market with over 28% share, pioneering cloud‑native solutions like PolarDB and RDS, while public‑cloud deployments surpass traditional on‑premises databases, a trend expected to reach 73.5% by 2025.
This article provides a comprehensive overview of relational database fundamentals, covering common DBMS products, SQL language components, integrity constraints, transactions, locking, views, stored procedures, indexes, normalization, key differences, constraints, optimization techniques, storage engines, and performance strategies for high‑traffic sites.
The article explains why relational databases, especially PostgreSQL combined with TimescaleDB, are better suited than NoSQL for handling complex, time‑series IoT data, offering robust SQL ecosystems, schema design, data integrity, and reduced data silos for multi‑user access.
This article provides a comprehensive interview‑style overview of MySQL fundamentals, covering relational database concepts, data types, storage engines, SQL syntax, version checking, normal forms, views, stored procedures, and performance tips, all essential for backend developers and database professionals.
This article chronicles the ten‑year evolution of OceanBase, a distributed relational database created by Sun Zhenkun and his team, detailing early challenges, technical breakthroughs, benchmark victories like TPC‑C world records, and its impact on Alibaba’s financial systems.
The article traces how each mobile generation—from 1G’s early relational databases to 2G’s open‑source RDBMS, 3G’s scalable NoSQL, 4G’s NewSQL hybrids, and the emerging 5G era demanding ultra‑low latency, cloud‑native, AI‑driven real‑time analytics—shapes database architecture and future trends.
The article chronicles OceanBase’s evolution from a research project to a commercial distributed relational database, detailing the technical challenges of meeting strict transaction, consistency, and availability requirements, the innovative solutions adopted, key milestones, and its impact on Alibaba’s ecosystem and the broader market.
This article walks through choosing a web framework and database, introduces relational databases, explains design steps such as requirement analysis, table creation, primary key selection, relationship modeling (one‑to‑many, many‑to‑many, one‑to‑one) with SQL examples, and covers normalization forms, integrity rules, and indexing strategies.
The article summarizes a 2017 BDTC conference talk by Ant Financial senior researcher Yang Zhenkun, detailing the challenges of traditional relational databases and presenting OceanBase's distributed, high‑availability, cost‑effective solutions for large‑scale financial systems.
This article explains the inner workings of relational databases, covering their core components, query optimization flow, indexing, merge sort, transaction handling, concurrency control, and lock management, while illustrating concepts with examples and diagrams.
This article introduces MySQL and MongoDB, compares their characteristics, and demonstrates simple CRUD commands for each, helping developers understand when to choose a relational versus a non‑relational database based on business needs.
The article compares relational databases like MySQL—highlighting their consistency, transaction support, and join capabilities—with NoSQL alternatives, explaining each type’s strengths and limitations in handling massive writes, schema changes, variable fields, and simple queries, and guides developers on when to choose each.
