Estimated reading time: 18 minutes

This case study covers a data exploration and analysis scenario about modeling data when migrating to ArangoDB. The topics covered in this case study include:

• Importing data into ArangoDB
• Developing Application Requirements before modeling
• Data Analysis and Exploration with AQL

This case study can hopefully be used as a guide as it shows step-by-step instructions and discusses the motivations in exploring and transforming data in preparation for a real-world application.The information contained in this case study is derived from the development of the..

Estimated reading time: 10 minutes

This is a short tutorial to get started with ArangoDB using Node.js. In less than 10 minutes you can learn how to use ArangoDB with Node. This tutorial uses a free ArangoDB Sandbox running on ArangoGraph that requires no sign up.

Estimated reading time: 6 minutes

Nothing performs faster than arangoimport and arangorestore for bulk loading or massive inserts into ArangoDB. However, if you need to do additional processing on each row inserted, this blog will help with that type of functionality.

If the data source is a streaming solution (such as Kafka, Spark, Flink, etc), where there is a need to transform data before inserting into ArangoDB, this solution will provide insight into that scenario as well.

Let’s delve into the specifics.

Version 6.0.0 of the JavaScript driver arangojs is now available (Find it on GitHub).

This is a major release that introduces a small number of breaking changes so make sure to check out the arangojs changelog before upgrading. The most significant additions in this release are support for load balancing and automated failover as well as improved browser and TypeScript support.

The first alpha of the official JavaScript driver arangojs‘ upcoming major release is now available on npm.

Version 4 streamlines the driver’s API by removing unnecessary server roundtrips to obtain references to collections and graphs that already exist:

Before:

var db = require('arangojs')(); db.collection('users') .then(function(collection) { return collection.import(allTheUsers) }) .then(function() { return db.collection('blogs') }) .then(function(collection) { return collection.import(allTheBlogs); }) .then(function() { return db.collection('articles') }) .then(function(collection) {..

ArangoDB allows running user-defined JavaScript code in the database. This can be used for more complex, stored procedures-like database operations. Additionally, ArangoDB’s Foxx framework can be used to make any database functionality available via an HTTP REST API. It’s easy to build data-centric microservices with it, using the scripting functionality for tasks like access control, data validation, sanitation etc.

We often get asked how the scripting functionality is implemented under the hood. Additionally, several people have asked how ArangoDB’s JavaScript functionality relates to..

ArangoDB 2.6 uses V8 engine version 3.31.74.1 for running its own and all user-defined JavaScript code. In ArangoDB 2.7 (currently in development), we have upgraded V8 to version 4.3.61.

The new V8 version in ArangoDB 2.7 provides several additional ES6 Harmony features that can be used to improve JavaScript usability and code quality. This blog post showcases strong mode and rest parameters, and also shows how to activate TurboFan, V8’s new JIT compiler for JavaScript.

ArangoDB 2.7 is in development right now, but it can be tried today by compiling it from source.

ArangoJS, the official ArangoDB JavaScript client, has been updated to version 3.7.0. The new release features significant performance improvements in Node.js and io.js. The dependency on the third-party request module has been replaced with a thin wrapper around node’s own http module, bringing a 3-4x performance improvement for consecutive requests by maintaining a connection pool.

The latest update to the AQL Query Builder for JavaScript addresses a major pain point: the “prefix notation” or LISP style syntax of AQL operator methods. Instead of calling the operator methods on the query builder object itself, you can now directly call them as methods on value objects.

Let’s say you want to write a query that takes all non-admin users with a power level over 9000 and returns their score rounded to the closest 100. In plain AQL this could be written like this:

FOR user IN users
FILTER user.isAdmin == false && user.powerLevel > 9000
RETURN ROUND(user.score / 100) * 100

..

The fans of modern and agile software development usually propose to use schemaless database engines to allow for greater flexibility, in particular during the early rapid prototyping phase of IT projects. The more traditionally minded insist that having a strict schema that is enforced by the persistence layer throughout the lifetime of a project is necessary to ensure quality and security.In this post I would like to explain briefly, why I believe that both groups are completely right and why this is not so paradoxical as it sounds at first glance. I am one of the developers of ArangoDB,..