Data and Query Basics

A comparative introduction to organizing and querying data in relational and graph databases.

Organizing data

Relational and graph databases organize data is distinctly different ways.

Relational databases

Traditional relational databases divide data into tables, columns, and rows.

Graph databases

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.

Example using a family tree

A family tree database stores data representing individuals, their parents, and grandparents.

Relational databases

The table below represents a model for storing this scenario in a relational database.

Graph databases

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.

Table: Family tree in a relational database

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

Diagram: Family tree in a graph database

Querying data

Relational database queries

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.

Graph database 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

Code: Family tree traversal using SQL

select  name 
from table_name 
where person_id = (
        select  mother_id
        from table_name 
        where name = "Bob")

select  name 
from table_name 
where person_id = (
        select mother_id
        from table_name 
        where person_id = (
                select mother_id
                from table_name 
                where name = "Bob"))

Code: Family tree traversal using WOQL

WOQL.and
(
   WOQL.triple("v:person", "mother", "v:mother_id"),
   WOQL.triple("v:mother_id", "name", "v:mother_name"),
   WOQL.triple("v:mother_id", "mother", "v:grandmother_id"),
   WOQL.triple("v:grandmother_id", "name", "v:grandmother_name"),
)