The ArangoDB query language (AQL) can be used to retrieve and modify data that are stored in ArangoDB.
A client application ships an AQL query to the ArangoDB server.The query text contains everything ArangoDB needs to compile the result set
ArangoDB will parse the query, execute it and compile the results. If the query is invalid or cannot be executed, the server will return an error that the client can process and react to. If the query can be executed successfully, the server will return the query results (if any) to the client
ArangoDB is a native multi-model database. Multi-model because ArangoDB provides the capabilities of a graph database, a document database, a key-value store in one C++ core. It’s native, because users can use and freely combine all supported data models and access patterns in a single query.
The dataset features 43 characters with their name, surname, age, alive status and trait references. The surname and age properties are not always present.
The column traits (resolved) is not part of the actual data used in this tutorial, but included for your convenience.
This manual describes the ArangoDB importer arangoimp, which can be used for bulk imports. The most convenient method to import a lot of data into ArangoDB is to use the arangoimp command-line tool. It allows you to import data records from a file into an existing database collection.
In its purpose, AQL is similar to the Structured Query Language (SQL). AQL supports reading and modifying collection data, but it doesn't support data-definition operations such as creating and dropping databases, collections and indexes. It is a pure data manipulation language (DML), not a data definition language (DDL) or a data control language (DCL).
Thinking about your data as a highly connected set of information is a powerful way to gain insights, solve problems and bring products faster into the hands of your users.
Unlike other databases, relationships take the first priority in graph databases and with ArangoDBs multi-model approach for graphs, documents and key/value pairs you can even switch between models or combine them in a single query.
ArangoDB comes with a command-line tool utility named arangoimp. This utility can be used for importing JSON-encoded, CSV, and tab-separated files into ArangoDB.
arangoimp needs to be invoked from the command-line once for each import file. The target collection can already exist or can be created by the import run.
This chapter describes the general-graph module. It allows you to define a graph that is spread across several edge and document collections. This allows you to structure your models in line with your domain and group them logically in collections giving you the power to query them in the same graph queries. There is no need to include the referenced collections within the query, this module will handle it for you.
ArangoDB provides several ways to query graph data. Very simple operations can be composed with the low-level edge methods edges, inEdges, and outEdges for edge collections. These work on named and anonymous graphs. For more complex operations, ArangoDB provides predefined traversal objects.
use a traversal object, we first need to require the traversal module:var traversal = require("@arangodb/graph/traversal"); var examples = require("@arangodb/graph-examples/example-graph.js"); examples.loadGraph("worldCountry");
The errorResponse method provided by controller request contexts has no equivalent in router endpoints.
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