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+= A Relational Model of Data for Large Shared Data Banks - article-review
+
+:empty:
+:reviewed-article: https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf
+
+This is a review of the article "{reviewed-article}[A Relational Model of Data
+for Large Shared Data Banks]", by E. F. Codd.
+
+== Data Independence
+
+Codd brings the idea of _data independence_ as a better approach to use on
+databases.  This is contrast with the existing approaches, namely hierarquical
+(tree-based) and network-based.
+
+His main argument is that queries in applications shouldn't depende and be
+coupled with how the data is represented internally by the database system.
+This key idea is very powerful, and something that we strive for in many other
+places: decoupling the interface from the implementation.
+
+If the database system has this separation, it can kep the querying interface
+stable, while having the freedom to change its internal representation at will,
+for better performance, less storage, etc.
+
+This is true for most modern database systems.  They can change from B-Trees
+with leafs containing pointers to data, to B-Trees with leafs containing the raw
+data , to hash tables.  All that without changing the query interface, only its
+performance.
+
+Codd mentions that, from an information representation standpoint, any index is
+a duplication, but useful for perfomance.
+
+This data independence also impacts ordering (a _relation_ doesn't rely on the
+insertion order).
+
+== Duplicates
+
+His definition of relational data is a bit differente from most modern database
+systems, namely *no duplicate rows*.
+
+I couldn't find a reason behind this restriction, though.  For practical
+purposes, I find it useful to have it.
+
+== Relational Data
+
+:edn: https://github.com/edn-format/edn
+
+In the article, Codd doesn't try to define a language, and today's most popular
+one is SQL.
+
+However, there is no restriction that says that "SQL database" and "relational
+database" are synonyms.  One could have a relational database without using SQL
+at all, and it would still be a relational one.
+
+The main one that I have in mind, and the reason that led me to reading this
+paper in the first place, is Datomic.
+
+Is uses an {edn}[edn]-based representation for datalog
+queries{empty}footnote:edn-queries[
+  You can think of it as JSON, but with a Clojure taste.
+], and a particular schema used to represent data.
+
+Even though it looks very weird when coming from SQL, I'd argue that it ticks
+all the boxes (except for "no duplicates") that defines a relational database,
+since building relations and applying operations on them is possible.
+
+Compare and contrast a contrived example of possible representations of SQL and
+datalog of the same data:
+
+[source,sql]
+----
+-- create schema
+CREATE TABLE people (
+  id UUID PRIMARY KEY,
+  name TEXT NOT NULL,
+  manager_id UUID,
+  FOREIGN KEY (manager_id) REFERENCES people (id)
+);
+
+-- insert data
+INSERT INTO people (id, name, manager_id) VALUES
+  ("d3f29960-ccf0-44e4-be66-1a1544677441", "Foo", "076356f4-1a0e-451c-b9c6-a6f56feec941"),
+  ("076356f4-1a0e-451c-b9c6-a6f56feec941", "Bar");
+
+-- query data, make a relation
+
+SELECT employees.name AS 'employee-name',
+       managers.name AS 'manager-name'
+FROM people employees
+INNER JOIN people managers ON employees.manager_id = managers.id;
+----
+
+[source,clojure]
+----
+;; create schema
+#{{:db/ident       :person/id
+   :db/valueType   :db.type/uuid
+   :db/cardinality :db.cardinality/one
+   :db/unique      :db.unique/value}
+  {:db/ident       :person/name
+   :db/valueType   :db.type/string
+   :db/cardinality :db.cardinality/one}
+  {:db/ident       :person/manager
+   :db/valueType   :db.type/ref
+   :db/cardinality :db.cardinality/one}}
+
+;; insert data
+#{{:person/id      #uuid "d3f29960-ccf0-44e4-be66-1a1544677441"
+   :person/name    "Foo"
+   :person/manager [:person/id #uuid "076356f4-1a0e-451c-b9c6-a6f56feec941"]}
+  {:person/id      #uuid "076356f4-1a0e-451c-b9c6-a6f56feec941"
+   :person/name    "Bar"}}
+
+;; query data, make a relation
+{:find [?employee-name ?manager-name]
+ :where [[?person  :person/name    ?employee-name]
+         [?person  :person/manager ?manager]
+         [?manager :person/name    ?manager-name]]}
+----
+
+(forgive any errors on the above SQL and datalog code, I didn't run them to
+check.  Patches welcome!)
+
+This employee example comes from the paper, and both SQL and datalog
+representations match the paper definition of "relational".
+
+Both "Foo" and "Bar" are employees, and the data is normalized.  SQL represents
+data as tables, and Datomic as datoms, but relations could be derived from both,
+which we could view as:
+
+[source,sql]
+----
+employee_name | manager_name
+----------------------------
+"Foo"         | "Bar"
+----
+
+== Conclusion
+
+The article also talks about operators, consistency and normalization, which are
+now so widespread and well-known that it feels a bit weird seeing someone
+advocating for it.
+
+I also stablish that `relational != SQL`, and other databases such as Datomic
+are also relational, following Codd's original definition.