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Three Ways to Scale your Graph

Estimated reading time: 10 minutes

Estimated reading time: 10 minutes

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Using the WebUI AQL Editor – Basics

Estimated reading time: 3 minutes

The ArangoDB query language (AQL) can be used to retrieve and modify data that is stored in ArangoDB. The AQL editor in the web interface is useful for running ad hoc AQL queries and trying things out.

The editor is split into three parts. The center section allows you to write your query and modify your query bind parameters. At the bottom you can either run the query or explain it, allowing to explain the query and inspect its execution plan. This can be used to check if the query uses indexes, and which. Here more information about optimizing a query.

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A geo demonstration using Foxx

Estimated reading time: 2 minutes

Geo data is getting more and more important for today’s applications. The growing number of location-aware services, IoT applications and other solutions using latitude and longitude ask for precise and fast processing of geo data.

Let me show you in this quick demonstration how you can use geo functions and visualize your data using Foxx and leaflet.js.

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Create an ArangoDB cluster on Microsoft Azure

Estimated reading time: 3 minutes

During the last weeks we’ve released our new deployment tool for cloud computing platforms with how-to’s for Google Compute Engine, Digital Ocean and Amazon Web Services support.

Today we show how to deploy an ArangoDB cluster on Azure with a single command.

Azure

To easy-deploy an ArangoDB cluster on Azure you just need to install the official azure-cli, download a single bash script and watch the tool take care of the rest for you. Your azure account needs permission for creating instances, adding ssh-keypairs and managing virtual networks.

wget..
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Create an ArangoDB cluster on Amazon Web Services (AWS)

Estimated reading time: 2 minutes

During the last weeks we’ve released our new deployment tool for cloud computing platforms with how-to’s for Google Compute Engine and Digital Ocean support.

Today we show how to deploy an ArangoDB cluster on Amazon Web Services with a single command.

Amazon Web Services (AWS)

To easy-deploy an ArangoDB cluster on AWS you just need to install the official awscli, download a single bash script and watch the tool take care of the rest for you. Your aws account needs permission for creating instances, adding ssh-keypairs and managing security groups.

wget..
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Create an ArangoDB cluster on Google Compute Engine with a single command

Estimated reading time: 3 minutes

Last week we’ve released the first version of our new deployment tool for cloud computing platforms with Digital Ocean support. (Edit: now also available: Amazon Web Services) Today we show how to deploy an ArangoDB cluster on Google Compute Engine with a single command.

Google Compute Engine

To easy-deploy an ArangoDB cluster on Google Compute Engine you just need to install the official gcloud tool, download a single bash script and watch the tool take care of the rest for you.

wget https://raw.githubusercontent.com/ArangoDB/deployment/publish/GoogleComputeEngine_ArangoDB_Cluster.sh chmod..
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Create an ArangoDB cluster on Digital Ocean with a single command

Estimated reading time: 2 minutes

It is often difficult and time-consuming to setup a cluster environment for development or production purposes. For this reason, we decided to make an initial setup for you as easy as possible.

Today we’re introducing the first part of our new deployment tool for cloud computing platforms (Edit: now also available: Amazon Web Services and Google Compute Engine):

Part 1: Digital Ocean

We’ve released our first prototype, which deploys an ArangoDB Cluster on Digital Ocean. Just download a single bash script, export your Digital Ocean API Token and watch the tool take care of the rest for you.

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