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Maintenance Release – ArangoDB v2.5.2

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This version is deprecated. Download the new version of ArangoDB

A maintenance release of ArangoDB 2.5 is available for download. The latest v2.5.2 comes with cluster speedups, some fixes in cluster mode and improved graph queries.

You can start an ArangoDB cluster on Digital Ocean with a single command, other cloud services will follow in the next days. Please try the new release, maybe on Digital Ocean with the new cluster setup script, and provide us your feedback.

Which cloud provider should we support next?

Here are the changes in the current maintenance release:

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Create an ArangoDB cluster on Digital Ocean with a single command

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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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Be more lazy, use a custom .arangod.rc

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How often did you typed

var db = require("internal").db;

in the arangod console?

If you are familiar with the arangosh JavasScript shell than you probably use a custom .arangosh.rc startup script in your home-directory which defines your own extra variables and functions that you need often.

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More Efficient Data Exports with new Export API

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ArangoDB 2.6 provides a specialized export API for exporting all documents from a collection and shipping them to a client application. It is rather limited but faster than the general-purpose AQL cursor API and can store its snapshots using less memory.

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New Cursor API leads to significant performance improvements

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This week we pushed some modifications for ArangoDB’s cursor API into the devel branch. The change will result in less copying of AQL query results between the AQL and the HTTP layers. As a positive side effect, this will reduce the amount of garbage collection the built-in V8 has to do.

These modifications should improve the cursor API performance significantly for many cases, while at the same time keeping its REST API stable. Client programs do not need to be adjusted to reap the benefits. In a blog post, Jan shows some first unscientific performance tests comparing the old cursor API with..

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AQL: Improved data-modification queries

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Data-modification queries were enhanced in ArangoDB 2.4 to be able to also return the inserted, update or removed documents. For example, the following statement inserted a few documents and also returned them with all their attributes:

FOR i IN 1..10
  INSERT { value: i } IN test
  LET inserted = NEW
  RETURN inserted

The syntax for returning documents from data-modification queries only supported the exact above format. Using a LET clause was required, and the RETURN clause was limited to returning the variable introduced by the LET. These syntax restrictions have been lifted in the devel..

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Preview of the UPSERT Command

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This week saw the completion of the AQL UPSERT command. This command will be very helpful in a lot of use cases, including the following:

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Slides: Is multi-model the future of NoSQL?

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Here is a slideshare and recording of my talk about multi-model databases, presented in Santa Clara earlier this month.

Abstract: Recently a new breed of “multi-model” databases has emerged. They are a document store, a graph database and a key/value store combined in one program. Therefore they are able to cover a lot of use cases which otherwise would need multiple different database systems. This approach promises a boost to the idea of “polyglot persistence“, which has become very popular in recent years although it creates some friction in the form of data conversion and synchronisation..

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Graphs in data modeling 

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Max wrote an inspiring article about graphs in data modeling on Medium, packed with his own thoughts – “to sort out some things in my brain” (Max).

He asks and answers the question: Are graphs and graph databases useful in data modeling, and if so, for what and under which circumstances?

In his article, he goes all the way down from the theoretical approach of what is a graph? towards storing a graph in different storage models (RDBMS, document store and graph databases) to querying a graph and finally to his personal conclusion.

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ArangoDB 2.5.1 available

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A new release of ArangoDB is available for download.

ArangoDB 2.5.1 adds slow-query log and killing running queries to the Http API and to the web-interface. We have also fixed inefficiencies in remove methods of the general-graph module and solved some issues regarding stability on windows. The added option --database.ignore-logfile-errors controls how collection datafiles with a CRC mismatch are treated. We recommend to upgrade your 2.5.0 installation to benefit from these improvements.

ArangoDB 2.5.1 could be started from..

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