Dockerizing a Bloom-based Nonces Service in 10 Minutes

In this article I want to explain how to setup a nonce-microservice using docker.

Nonce are one-time tokens that are used to ensure that an action can only be taken once. In a project, we needed to ensure that a pay button is only pressed once. Note that nonces are not used to sign requests or identify a user. This is a separate mechanism.

ArangoDB contains a nonce implementation which is a variation of Bloom-filters. It allows to store nearly unlimited nonces within a limited amount of memory. Nonce are allowed to age, that is after an hour they might expire. If there is sufficient interest, I will explain the algorithm implemented in a separate blog post.

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Create an ArangoDB cluster on Microsoft Azure

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.

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ArangoDB 2.6 – API changes, additions and changed behavior

ArangoDB 2.6 comes with new and changed APIs as well as changed behavior regarding document keys and several graph functions.

If you use Travis-CI for your tests you can download the Travis-CI ArangoDB build here: Travis-CI/ArangoDB-2.6.0-alpha2.tar.gz

The changes so far:

APIs added

  • added batch document removal and lookup APIs:

    These APIs can be used to perform multi-document lookup and removal operations efficiently. The arguments to these APIs are the name of the collection plus the array of document keys to fetch or remove.

    The endpoints for these APIs are as follows:

    Example call to fetch documents:

    The documents will be returned in an attribute documents of the HTTP response. documents is an array containing all documents found. Only those documents that were actually found will be returned. Documents that were searched but do not exist will not be returned and do not trigger any errors. (more…)

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Web Interface supports AQL Query Explain

For developers that use the ArangoDB shell arangosh the explain() command and its compact output format is a great resource to check AQL queries. Explain prints the original query, the generated query execution plan, the applied optimizer rules plus the list of indexes that will be used. Jan showed in a blog post how this can look like.

While preparing ArangoDB 2.6 we found some time to add this feature to the Web UI. So now you can check you AQL queries right in the Web-Interface as well. (more…)

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Improved System User Authentication

ArangoDB can easily be configured to require HTTP authentication for access to the web admin frontend or the REST API. But while Basic Auth works fine for APIs, the user experience in the web admin frontend was decidedly sub-par: browsers would often persist the authentication credentials indefinitely, logging out was made difficult or impossible and switching users was hit-or-miss.

The upcoming ArangoDB 2.6 release introduces cookie-based authentication for the web admin frontend, allowing you to side-step the issue altogether by using the built-in session manager instead of the low-level HTTP API authentication. (more…)

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Create an ArangoDB cluster on Amazon Web Services (AWS)

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.

(more…)

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Creating Multi-Game Highscore Lists

I just came across a question about how to create highscore lists or leaderboards in ArangoDB, and how they would work when compared to Redis sorted sets.

This blog post tries to give an answer on the topic and also detailed instructions and queries for setting up highscore lists with ArangoDB. The additional section “Extensions” explains slightly more advanced highscore list use cases like multi-game highscore lists, joining data and maintaining a “last updated” date.
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Posted in API, Documentation, Query Language | 3 Comments

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

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.

Google Compute Engine prerequisites

The script needs an available and configured Google Project.

ProjectID
  • Create a project (GCE Projects).
  • Remember your project-id, you’ll need that later for gcloud configuration.
  • Enable Google Compute Engine API (more…)

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Updating Documents with an Arangoimp Import

Inspired by the feature request in Github issue #1298, we added update and replace support for ArangoDB’s import facilities.

This extends ArangoDB’s HTTP REST API for importing documents plus the arangoimp binary so they can not only insert new documents but also update existing ones.

Inserts and updates can also be mixed in a single import run. What exactly will happen is configurable by setting arangoimp’s new command-line option --on-duplicate.

By default, error will be reported if a document already exists. This behavior can be changed by setting --on-duplicate to a value of update, replace or ignore. Here is an example result of an import with duplicated keys:

So, if you want to aggregate data from several data files, you can try the new import command-line option --on-duplicate.

In a blog post, Jan provides a few usage examples.

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Create an ArangoDB cluster on Digital Ocean with a single command

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.

(more…)

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