Configuring ArangoDB-PHP to use active failover
This article is about setting up active failover for ArangoDB-PHP, the PHP client driver for ArangoDB. It requires ArangoDB-PHP 3.3.2 or higher, and an ArangoDB server version of 3.3.4 or higher.
Interested in trying out ArangoDB? Fire up your cluster in just a few clicks with ArangoDB ArangoGraph: the Cloud Service for ArangoDB. Start your free 14-day trial here
Active failover: basic setup
Historically, ArangoDB-PHP has been able to connect to a single ArangoDB endpoint, i.e. one combination of IP address and port number.
To connect to an ArangoDB server that is running on localhost or on a remote server, simply set the `OPTION_ENDPOINT` item in the `ConnectionOptions` and connect: Read more
ArangoDB | Milestone2: ArangoDB 3.3 New Data Replication
We’re pleased to announce the availability of the Milestone 2 of ArangoDB 3.3. There are a number of improvements, please consult the changelog for a complete overview of changes.
This milestone release contains our new and improved data replication engine. The replication engine is at the core of every distributed ArangoDB setup: whether it is a typical master/slave setup between multiple single servers or a full-fledged cluster. During the last month we:
- redesigned the replication protocol to be more reliable
- refactored and modernized the internal infrastructure to better support continuous asynchronous replication
- added a new global asynchronous replication API, to allow you to automatically and continuously mirror an entire ArangoDB single-instance (master) onto another one (or more)
- added support for automatic failover from a master server to one of his replica-slaves, if the master server becomes unreachable
Milestone 1 ArangoDB 3.3: Datacenter to Datacenter Replication
Every company needs a disaster recovery plan for all important systems. This is true from small units like single processes running in some container to the largest distributed architectures. For databases in particular this usually involves a mixture of fault-tolerance, redundancy, regular backups and emergency plans. The larger a data store, the more difficult is it to come up with a good strategy.
Therefore, it is desirable to be able to run a distributed database in one datacenter and replicate all transactions to another datacenter in some way. Often, transaction logs are shipped over the network to replicate everything in another, identical system in the other datacenter. Some distributed data stores have built-in support for multiple datacenter awareness and can replicate between datacenters in a fully automatic fashion.
This post gives an overview over the first evolutionary step of ArangoDB towards multi-datacenter support, which is asynchronous datacenter to datacenter replication.
Setting up Datacenter to Datacenter Replication in ArangoDB
Please note that this tutorial is valid for the ArangoDB 3.3 milestone 1 version of DC to DC replication!
Interested in trying out ArangoDB? Fire up your cluster in just a few clicks with ArangoDB ArangoGraph: the Cloud Service for ArangoDB. Start your free 14-day trial here
This milestone release contains data-center to data-center replication as an enterprise feature. This is a preview of the upcoming 3.3 release and is not considered production-ready.
In order to prepare for a major disaster, you can setup a backup data center that will take over operations if the primary data center goes down. For a server failure, the resilience features of ArangoDB can be used. Data center to data center is used to handle the failure of a complete data center.
Data is transported between data-centers using a message queue. The current implementation uses Apache Kafka as message queue. Apache Kafka is a commonly used open source message queue which is capable of handling multiple data-centers. However, the ArangoDB replication is not tied to Apache Kafka. We plan to support different message queues systems in the future.
The following contains a high-level description how to setup data-center to data-center replication. Detailed instructions for specific operating systems will follow shortly. Read more
Webinar: Use ArangoDB Agency as fault-tolerant persistent data store
Join our Sr Distributed System Engineer, Kaveh Vahedipour, to learn more about ArangoDB Agency on September 19th, 2017 (6PM CEST/12PM ET/ 9AM PT) – View the Recording.
Distributed systems have become the standard topology on which modern appliances live. While the advantages of distributing workload for both performance as well as fault-tolerance are obvious, the runtime flexible configuration of such deployment becomes non-trivial.
ArangoDB clusters are no different in that regard. A potentially large database cluster’s configuration is manipulated at runtime by addition, alteration and removal of collections, indexes, and even servers. All servers need to trust in a fault-tolerant centralized configuration tree, which we call “the agency” in arango-speak. Read more
ArangoDB | Pronto Move Shard – Multi-Model NoSQL Database
In July Adobe announced that they plan the End-of-Life for flash at around 2020.
As HTML5 progressed and due to a long history of critical security vulnerabilities this is – technologically speaking – certainly the right decision. However I tended to also become a bit sad.
Flash was the first technology that brought interactivity to the web. We tend to forget how static the web was in the early 2000s. Flash brought life to the web and there were plenty of stupid trash games and animations which I really enjoyed at the time. As a homage to the age of trashy flash games I created a game which resembles the games of this era: Read more
The new SatelliteCollections Feature of ArangoDB
With the new Version 3.2 we have introduced a new feature called SatelliteCollections. This post explains what this is all about, how it can help you, and explains a concrete use case for which it is essential.
Background and Overview
Join operations are very useful but can be troublesome in a distributed database. This is because quite often, a join operation has to bring together different pieces of your data that reside on different machines. This leads to cluster internal communication and can easily ruin query performance. As in many contexts nowadays, data locality is very important to avoid such headaches. There is no silver bullet, because there will be many cases in which one cannot do much to improve data locality.
One particular case in which one can achieve something, is if you need a join operation between a very large collection (sharded across your cluster) and a small one, because then one can afford to replicate the small collection to every server, and all join operations can be executed without network communications.
ArangoDB 3.2 Beta: RocksDB Storage Engine & Distributed Graph Cluster
We’re excited to release today the beta of ArangoDB 3.2. It’s feature rich, well tested and hopefully plenty of fun for all of you. Keen to take it for a spin? Get ArangoDB 3.2 beta here.
With ArangoDB 3.2, we’re introducing the long-awaited pluggable storage engine and its first new citizen, RocksDB from Facebook
- RocksDB: You can now use as much data in ArangoDB as you can fit on your disk. Plus, you can enjoy performance boosts on writes by having only document-level locks (more info below).
- Pregel: Furthermore, we implemented distributed graph processing with Pregel for discovering hidden patterns, identify communities and perform in-depth analytics of large graph data sets.
- ClusterFoxx: Another important upgrade is what we internally and playfully call the ClusterFoxx. The Foxx management internals have been rewritten from the ground up to make sure multi-coordinator cluster setups always keep their services in sync and new coordinators are fully initialised even when all existing coordinators are unavailable.
- Enterprise: Working with some of our largest customers, we’ve added further security and scalability features to ArangoDB Enterprise like LDAP integration, Encryption at Rest, and the brand new Satellite Collections.
The goal of the whole ArangoDB 3 release cycle has been to scale the multi-model idea to new heights. Getting ‘ready’ for large scale applications is not done overnight and it’s definitely not possible without the help of a strong community. We’d like to invite all of you to lend us a helping hand to make ArangoDB 3.2 the best release ever. Please push this beta to its limits: test it for your use cases and compare the performance of the new features like RocksDB. Let us know on Github any bug that you find. Don’t worry about hurting our feelings: we want to fix any problems.
Join the Beta Bug Hunt Challenge and win a $200 Amazon Gift Card as first prize. You can find more details about this reward program at the end of this post. Read more
ArangoDB: Consensus for Enhanced Data Stability
– law of the polish-lithuanian common-wealth, 1505
A warning aforehand: this is a rather longish post, but hang in there it might be saving you a lot of time one day.
Introduction
Consensus has its etymological roots in the latin verb consentire, which comes as no surprise to mean to consent, to agree. As old as the verb equally old is the concept in the brief history of computer science. It designates a crucial necessity of distributed appliances. More fundamentally, consensus wants to provide a fault-tolerant distributed animal brain to higher level appliances such as deployed cluster file systems, currency exchange systems, or specifically in our case distributed databases, etc. Read more
Starting an ArangoDB cluster the easy way
Recently, we have got a lot of feedback about the fact that standing up an ArangoDB cluster “manually” is an awkward and error-prone affair. We have been aware of this for some time, but always expected that most users running ArangoDB clusters would do so on Apache Mesos or DC/OS, where deployment is a breeze due to our ArangoDB framework.
However, for various valid reasons people do not want to use Apache Mesos and thus are back to square one with the problem of deploying an ArangoDB cluster without Apache Mesos. Read more
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