Data Model & Concepts
This chapter introduces ArangoDB’s core concepts and covers
- its data model (or data models respectively),
- the terminology used throughout the database system and in this documentation
You will also find usage examples on how to interact with the database system using arangosh, e.g. how to create and drop databases / collections, or how to save, update, replace and remove documents. You can do all this using the web interface as well and may therefore skip these sections as beginner.
ArangoDB is a database that serves documents to clients. These documents are transported using JSON via a TCP connection, using the HTTP protocol. A REST API is provided to interact with the database system.
The web interface that comes with ArangoDB, called Aardvark, provides graphical user interface that is easy to use. An interactive shell, called Arangosh, is also shipped. In addition, there are so called drivers that make it easy to use the database system in various environments and programming languages. All these tools use the HTTP interface of the server and remove the necessity to roll own low-level code for basic communication in most cases.
The documents you can store in ArangoDB closely follow the JSON format, although they are stored in a binary format called VelocyPack. A document contains zero or more attributes, each of these attributes having a value. A value can either be an atomic type, i. e. number, string, boolean or null, or a compound type, i.e. an array or embedded document / object. Arrays and sub-objects can contain all of these types, which means that arbitrarily nested data structures can be represented in a single document.
Documents are grouped into collections. A collection contains zero or more documents. If you are familiar with relational database management systems (RDBMS) then it is safe to compare collections to tables and documents to rows. The difference is that in a traditional RDBMS, you have to define columns before you can store records in a table. Such definitions are also known as schemas. ArangoDB is by default schema-less, which means that there is no need to define what attributes a document can have. Every single document can have a completely different structure and still be stored together with other documents in a single collection. In practice, there will be common denominators among the documents in a collection, but the database system itself doesn’t force you to limit yourself to a certain data structure. To check for and/or enforce a common structure ArangoDB supports optional schema validation for documents on collection level.
There are two types of collections: document collection (also refered to as vertex collections in the context of graphs) as well as edge collections. Edge collections store documents as well, but they include two special attributes, _from and _to, which are used to create relations between documents. Usually, two documents (vertices) stored in document collections are linked by a document (edge) stored in an edge collection. This is ArangoDB’s graph data model. It follows the mathematical concept of a directed, labeled graph, except that edges don’t just have labels, but are full-blown documents.
Collections exist inside of databases. There can be one or many databases. Different databases are usually used for multi tenant setups, as the data inside them (collections, documents etc.) is isolated from one another. The default database _system is special, because it cannot be removed. Database users are managed in this database, and their credentials are valid for all databases of a server instance.
Similarly databases may also contain view entities. A View in its simplest form can be seen as a read-only array or collection of documents. The view concept quite closely matches a similarly named concept available in most relational database management systems (RDBMS). Each view entity usually maps some implementation specific document transformation, (possibly identity), onto documents from zero or more collections.
Queries are used to filter documents based on certain criteria, to compute new data, as well as to manipulate or delete existing documents. Queries can be as simple as a “query by example” or as complex as “joins” using many collections or traversing graph structures. They are written in the ArangoDB Query Language (AQL).
Cursors are used to iterate over the result of queries, so that you get easily processable batches instead of one big hunk.