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Recently I've started to play with cayley and ArangoDB for their graph datastores.

While reading and watching videos about graph databases a question popped up into my mind: what makes a graph database so different (and "awesome") from a typical (and horrible) EAV store in normal SQL?

In this presentation, the following citation shows up:

a graph database is any storage system that provides index-free adjacency

But what does index-free adjacency mean exactly? And how does that affect performance or design?

With the following schema, all the queries listed in the slides are possible and super simple:

CREATE TABLE "graph" (
    "subject" TEXT NOT NULL,
    "predicate" TEXT NOT NULL,
    "object" TEXT NOT NULL
);

-- Give me all the vertex that go from "A":
SELECT "object" FROM "graph" WHERE "subject" = 'A';

-- Give me all the pairs connected by "C":
SELECT "subject", "object" FROM "graph" WHERE "predicate" = 'C';

-- Give me all the vertex that go to "B":
SELECT "subject" FROM "graph" WHERE "object" = 'B';

-- Give me all the vertex that go to "B" through "C":
SELECT "subject" FROM "graph" WHERE "object" = 'B' AND "predicate" = 'C';
Alix Axel
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1 Answers1

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well, to be honest index-free adjacency i basically a marketing buzzword. I agree, your examples are simple and possible, but using a graph database enables you to perform queries that will be not so easy to handle (and most of all very bad performing) on mysql. F.e. if you want to know the shortest path between two vertices in a graph you can't do it using mysql.

In ArangoDB it is one simple call:

GRAPH_SHORTEST_PATH("yourGraph", "StartVertex", "EndVertex")

If you are interested in the various functions ArangoDBs graph module provides i can recommend to read the graph manual and the examples, i am pretty sure you will find a lot of use cases where you would struggle to achieve the same in mysql.

florian
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