3 ms·

> There are really no unsolved problems (of note), so it's not interesting to academics. For anyone who likes SQL and is looking for a research topic, read abo

> There are really no unsolved problems (of note), so it's not interesting to academics. For anyone who likes SQL and is looking for a research topic, read about temporal databases and suggest some ways to handle DDL changes over time (e.g. adding a new NOT NULL column, or changing a relationship from one-to-many to many-to-many). Here is your starting bibliography: Richard Snodgrass, Developing Time-Oriented Database Applications in SQL. Hugh Darwen & C.J. Date, "An Overview and Analysis of Proposals Based on the TSQL2 Approach". Krishna Kulkarni & Jan-Eike Michels, "Temporal features in SQL:2011". Tom Johnston, Bitemporal Data Magnus Hagander, "A TARDIS for Your ORM": https://www.youtube.com/watch?v=TRgni5q0YM8 https://www.youtube.com/watch?v=TRgni5q0YM8 I would love to read what you come up with!

nickpeterson 9y ago
I would argue that [http://www.AnchorModeling.com http://www.AnchorModeling.com] is a pretty good take on it. I think it shares some genealogy with Fact-Based Modeling techniques (FCO-IM?). It has a really decent story for evolving the schema over time. I've read Darwen/Date, Snodgrass, and Johnston's (two books) on the subject. Johnston's seems the best practical choice, but they patented the ideas :/ That said, one could probably implement Johnston's model without violating patents if you ignore explicitly modeling the episode structure and just follow the theory. Date and Darwen make decent points about wanting to use the relational model rather than some baked-in concept, but ultimately they do almost no legwork on practically putting any of their notions to use. This seems to be par for the course on Date books. Weis and Johnston handle the problem more directly. They also tackle a harder problem overall (BiTemporal, vs just Temporal). Also Johnston is just easier to read than Date. (Side note, I feel like a blog where I just read chapters of Date writings and condense the content basic points would end in most of Date's arguments fitting in 50 pages. That said, Weis and Johnston still punted on schema evolution. Anchor Modeling sort of starts at supporting an evolving schema and moves outward from there. In Anchor modeling there isn't the traditional Temporal/Bi-temporal notion, but rather positors than have varying degrees of certainty about posits. There is basically a concurrence of facts that can be retracted or changed over time. Useful for modeling varying degrees of certainty or alternate perspectives on data. The downside of Anchor Modeling is that the datamodel is basically 6th normal form with a bunch of table valued functions, triggers, and views to aid in making it palatable for devs. Johnston sort of acknowledges this style in one of his books but I believe argues against the concept of an entities information being spread throughout various tables. In his mind, a table is a type, that is made of attributes (columns). Anchor modeling is more along the lines of 'Attributes are types', and you can relate them to form larger types. I wish there was more work on the ORM side supporting some of these concepts (Schema evolution and temporality).
jackfoxy 9y ago
Yes, I would agree, temporal databases is an interesting topic.

nickpeterson 9y ago

I would argue that [http://www.AnchorModeling.com http://www.AnchorModeling.com] is a pretty good take on it. I think it shares some genealogy with Fact-Based Modeling techniques (FCO-IM?). It has a really decent story for evolving the schema over time. I've read Darwen/Date, Snodgrass, and Johnston's (two books) on the subject. Johnston's seems the best practical choice, but they patented the ideas :/ That said, one could probably implement Johnston's model without violating patents if you ignore explicitly modeling the episode structure and just follow the theory. Date and Darwen make decent points about wanting to use the relational model rather than some baked-in concept, but ultimately they do almost no legwork on practically putting any of their notions to use. This seems to be par for the course on Date books. Weis and Johnston handle the problem more directly. They also tackle a harder problem overall (BiTemporal, vs just Temporal). Also Johnston is just easier to read than Date. (Side note, I feel like a blog where I just read chapters of Date writings and condense the content basic points would end in most of Date's arguments fitting in 50 pages. That said, Weis and Johnston still punted on schema evolution. Anchor Modeling sort of starts at supporting an evolving schema and moves outward from there. In Anchor modeling there isn't the traditional Temporal/Bi-temporal notion, but rather positors than have varying degrees of certainty about posits. There is basically a concurrence of facts that can be retracted or changed over time. Useful for modeling varying degrees of certainty or alternate perspectives on data. The downside of Anchor Modeling is that the datamodel is basically 6th normal form with a bunch of table valued functions, triggers, and views to aid in making it palatable for devs. Johnston sort of acknowledges this style in one of his books but I believe argues against the concept of an entities information being spread throughout various tables. In his mind, a table is a type, that is made of attributes (columns). Anchor modeling is more along the lines of 'Attributes are types', and you can relate them to form larger types. I wish there was more work on the ORM side supporting some of these concepts (Schema evolution and temporality).

jackfoxy 9y ago

Yes, I would agree, temporal databases is an interesting topic.