#ARANGODB REVIEW FULL#

Distributed graph processing via PregelĪrangoDB supports document, graph, and key/value data models.

Horizontal Scaling with Graph Data and Queries.

Each edge and vertex can contain complex data in the form of nested properties, and all graph functions are deeply integrated into the ArangoDB Query Language, (AQL).ĪrangoDB provides a broad spectrum of graph database features: By this approach combined with the edge index, ArangoDB is one of the few graph databases capable of horizontal scaling.

#ARANGODB REVIEW FULL#

Vertices and edges are both full JSON documents and can hold arbitrary data. In ArangoDB this is handled differently (if you want to take a technical dive into ArangoDB’s approach, see this article about index-free adjacency vs. Graph databases usually store edges connected to vertices directly at the vertex object. Using an edge index, ArangoDB can process graph queries very efficiently. Edges are then stored in a special edge collection.ĪrangoDB enables efficient and scalable graph query performance by using a special hash index on _from and _to attributes (i.e., an edge index). To build a relation (i.e., an edge) between two documents (i.e., vertices), both _id attributes are stored in a special edge document known as _from and _to attributes, forming a directed connection between two arbitrary vertices. The graph capabilities of ArangoDB are similar to a property graph database but add more flexibility in terms of data modeling as vertices and edges are both full JSON documents.įor each document, a unique _id attribute is stored automatically. And, due to its native multi-model approach, you can build high performance applications and scale horizontally with all three data models. You can combine different models in one query.

You can store your data as key/value pairs, graphs or documents and access any or all of your data using a single declarative query language. Unlike many NoSQL databases, ArangoDB is a native multi-model database.

Arangodb review