A comparative introduction to organizing and querying data in relational and graph databases.
Relational and graph databases organize data is distinctly different ways.
Traditional relational databases divide data into tables, columns, and rows.
Similar to other graph databases, TerminusDB organizes data in objects. Objects have properties, properties link to other objects. A network of interlinked objects forms a graph structure - the foundation of graph databases.
Using objects rather than cells enables the creation of databases that closely model the real world.
A family tree database stores data representing individuals, their parents, and grandparents.
The table below represents a model for storing this scenario in a relational database.
The diagram further below illustrates the equivalent graph database model. An advantage of the graph model is that it represents real-world objects more accurately, making the model intuitive and easier to understand.
Many relational databases use the Structured Query Language (SQL.) The example below uses a two-query approach to get the name of mother, then grandmother. Note the second query uses two nested sub-queries.
TerminusDB's purpose-built Web Object Query Language (WOQL) is an easier-to-use alternative to SQL. The example below demonstrates the same query using WOQL. WOQL uses triple patterns to get both names in one short query. There are no joins - joins are implied by using the same ID in different parts of the query. Using v:mother_id
multiple times creates the chain:
v:person_id = mother => v:mother = mother => v:grandmother
person_id
name
DOB
mother_id
father_id
1
Bob
01/10/1979
2
3
2
Zoe
04/02/1956
4
5
3
Bob Snr
28/11/1952
6
7
4
Ada
17/04/1922
NULL
NULL
5
Tom
01/09/1909
NULL
NULL
6
Eva
17/04/1923
NULL
NULL
7
Ray
03/10/1913
NULL
NULL