Comprehensive Overview of Database Technologies, History, Market Trends, and Cloud Migration

1. Databases and Database Management Systems

Upstream, databases rely on hardware such as minicomputers, microcomputers, storage devices, switches, routers, and IoT sensors; downstream, they are widely used in government, finance, energy, education, transportation and many other industries.

Databases can be divided into two major categories: relational databases and non‑relational (NoSQL) databases.

Relational databases (RDB) organize data in tables of rows and columns, making the model easy to understand; tables form a database, and users retrieve data through queries that translate high‑level requests into executable code.

NoSQL, a term for non‑relational databases, emerged to address the scalability and concurrency challenges of large‑scale web 2.0 applications, especially for big‑data workloads.

NoSQL offers advantages such as easy horizontal scaling, high read/write performance on massive data sets, and a simple schema due to the lack of relational constraints.

A Database Management System (DBMS) is a large‑scale software that creates, uses, and maintains databases, ensuring security and integrity.

DBMS provides data definition, manipulation, storage, maintenance, and communication functions, supporting multiple concurrent users and evolving alongside computer and network technologies.

DBMS operates based on a data model; its workflow includes:

(1) Receiving data requests from applications;

(2) Translating high‑level user requests into low‑level machine instructions;

(3) Executing database operations;

(4) Receiving query results;

(5) Processing (formatting) the results;

(6) Returning the processed results to the user.

Depending on the underlying model, DBMS can be hierarchical, network, relational, object‑oriented, etc., and different systems may expose varying interfaces and functionalities.

2. The Past and Present of Databases

Database technology originated abroad and was later introduced to China, resulting in distinct development paths. Internationally, three major stages are recognized: navigational databases, relational databases, and non‑relational databases, with autonomous databases representing a new dynamic.

First stage – Navigational Databases: In the 1960s, systems like IDS (Integrated Data Store) and IBM's IMS provided path‑guided data access without complex structures.

Second stage – Relational Databases (RDBMS): Edgar Codd proposed the relational model in 1970; subsequent milestones include Ingres, IBM's System R, DB2, Oracle (1978), and the standardization of SQL by ISO in 1987.

Third stage – NoSQL and NewSQL: The term NoSQL was coined in 1998 and revived in 2009 to describe distributed, schema‑flexible stores such as DynamoDB, MongoDB, Cassandra, and Redis. NewSQL combines the transactional guarantees of SQL with the scalability of NoSQL.

New dynamic – Autonomous (Self‑Driving) DBMS: In 2017, Carnegie Mellon’s Peloton project introduced self‑driving databases that use AI and machine‑learning to optimize workloads; Oracle later announced its Autonomous Database Cloud.

3. Database Market Size and Growth Potential

According to Gartner, the global database software market was $46.1 billion in 2018 and is projected to reach $54.9 billion by 2021, with a CAGR of 9.1 %.

In China, the market grew from ¥3.503 billion in 2009 to ¥149.91 billion in 2018, and is expected to reach ¥200 billion by 2020, driven by a 17.86 % average annual growth rate.

Foreign vendors still dominate, but domestic players have increased their share from 4.03 % in 2009 to 14.27 % in 2017, indicating a rising opportunity for Chinese database solutions.

4. Leading Database Vendors

DB‑Engines ranks Oracle first, followed by MySQL and Microsoft SQL Server; IBM DB2, SAP HANA and Adaptive Server also appear in the top rankings.

Gartner’s Magic Quadrant (2018) lists Amazon, Microsoft, Oracle, SAP, and IBM as leaders; Alibaba Cloud entered the Visionaries quadrant in 2019, becoming a notable challenger.

5. Cloud Migration as an Industry Trend

Gartner predicts cloud databases will account for 50 % of the market by 2021 and 75 % by 2023, reflecting a strong shift toward cloud‑based services.

Cloud databases are essentially traditional database engines (relational or NoSQL) offered as managed services, providing high scalability, availability, multi‑tenant isolation, and simplified operations.

Analysts note that on‑premise commercial databases face challenges of high cost, operational difficulty, and limited scalability, whereas cloud databases combine the elasticity of cloud computing with the openness of open‑source solutions.

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