The history of databases: a quick summary

Databases

The appearence of the term “database” coincided with the availability of direct-access storage (mid-60’s). The term represented a contrast with the tap-based systems of the past, allowing shared interactive use rather than batch processing.

Network databases

General purpose database systems emerged during that time.

CODASYL: primary key, navigation relationships, or scanning.

IBM IMS (Information Mamagement System), running on the System/360, initially developed for the Apollo program. Strictly hierarchical.

Both IMS and CODASYL classify as network databases.

1970’s relational databases

Edgar Codd, at the time working for IBM on storage, became frustrated by the limitations imposed by network databases.

Initial idea: tables of fixed-length records. Different table for different types of identity.

The relational part comes from the capability of entities can refer other entitities.

A relational database can express both hierarchical or navigational models, as well as its native tabular model.

To query it, the author of the relational algebra proposed a set-oriented languaged, which would later spawn SQL.

Based on Codd’s paper, INGRES was created by two people at Berkeley (Eugene Wong and Micheal Stonebraker).

Late 1970’s: SQL DBMSs

IBM started working on an implementation of Codd’s paper named System R, first single-table and then later, in the late 70’s, on a multi-table implementation.

Later, multi-user versions were developed and were tested by customers in 1978 and 1979, by which time a standardized language named SQL had been added.

The success of these experiments lead IBM to create a true production of System R known as SQL/DS and later, Database 2 (DB2).

By around the same time, Larry Ellison developed the Oracle database, based off IBM’s papers on System R, and released Oracle version 2 in 1979.

Stonebraker took his learnings from INGRES and started a project named Postgres (now known as PostgreSQL), since then used in many mission-critical applications.

1980’s on the desktop

Spreadsheet software (like Lotus 123) and database software (like dBASE) appeared for desktop computers. dBASE became a huge success during the 80’s and 90’s.

Document databases

Do not require fixed schemas, avoid join operations and are designed to scale horizontally.

Now

In recent years, there has been a strong for massively distributed databases with high partition tolerance. But the CAP theorem states that, in the presence of a network partition, you can either provide consistency or availability.

For that, many new databases are using what is called eventual consistency, guaranteeding availability during network partitions.