Abstract This paper provides a summary of 35 years of data model proposals, grouped into 9 different eras. We discuss the proposals of each era, and show that there are only a few basic data modeling ideas, and most have been around a long time. Later proposals inevitably bear a strong resemblance to certain earlier proposals. Hence, it is a worthwhile exercise to study previous proposals. In addition, we present the lessons learned from the exploration of the proposals in each era. Most current researchers were not around for many of the previous eras, and have limited (if any) understanding of what was previously learned. There is an old adage that he who does not understand history is condemned to repeat it. By presenting “ancient history”, we hope to allow future researchers to avoid replaying history. Unfortunately, the main proposal in the current XML era bears a striking resemblance to the CODASYL proposal from the early 1970’s, which failed because of its complexity. Hence, the current era is replaying history, and “what goes around comes around”. Hopefully the next era will be smarter.

There doesn't seem to be much discussion here. The interesting thing for me is actually that this paper is a part of the larger "Readings in Databse Systems"[1], a book composed of thin chapters discussing certain "mandatory" papers that you must read, if you want to have a deeper understanding of database systems.

It has been posted a lot on HN[2], but never quite got attention.

  [1] http://www.redbook.io/ch1-background.html
  [2] https://news.ycombinator.com/item?id=15436647

2023 version with the title ' M. Stonebraker, et al., What Goes Around Comes Around... And Around' is in the works.

See https://15721.courses.cs.cmu.edu/spring2023/schedule.html