We are thrilled to be attending one of Europe’s greatest events – JontheBeach (JOTB), an international rendezvous for developers and DevOps around Big Data technologies. No product talks just deep-tech topics presented by hand-picked speakers from Google, Apache Spark, RedHat, Stripe, Microsoft and many more.

We are absolutely thrilled to announce that one of the brightest and most respected minds in open-source software joins ArangoDBs Advisory Council. Hi, Ted and welcome to the ArangoDB family!For those who don’t know Ted Dunning yet, maybe a quick introduction and the reason why the whole team is so amazed that he supports the project. Ted Dunning is Chief Application Architect at MapR, holds a PhD in computer science and is committer as well as PMC member of the Apache Mahout, Zookeeper and Drill projects. Besides his 25 patents, and even more pending, he mentors multiple well-known Apache..

While working hard on the next release and hacking away new interesting things to include into our favourite database, we decided to take a short break to have some fun just in time for Easter. All teams gathered together to do some Easter eggs coloring, chocolate-eating and fun-having 🙂

The newest release 4.3.2 of the official ArangoDB Java driver comes with load balancing for cluster setups and advanced fallback mechanics.

Load balancing strategies

Round robin

There are two different strategies for load balancing that the Java driver provides. The first and most common strategy is the round robin way. Round robin does, what the name already assumes, a round robin load balancing where a list of known coordinators in the cluster is iterated through. Each database operation uses a different coordinator than the one before.

ArangoDB named by G2 Crowd users as the most popular graph database used today.

In this post, we will introduce you to our new ArangoDB C++ diver fuerte. fuerte allows you to communicate via HTTP and VST with ArangoDB instances. You will learn how to create collections, insert documents, retrieve documents, write AQL Queries and how to use the asynchronous API of the driver.

Requirements (Running the sample)

Please download and inspect the sample described in this post. The sample consists of a C++ – Example Source Code – File and a CMakeLists.txt. You need to install the fuerte diver, which can be found on github, into your system before compiling the sample. Please..

So you measured and tuned your system like described in the Part I and Part II of these blog post series. Now you want to get some figures how many end users your system will be able to serve. Therefore you define “scenarios” which will be typical for what your users do. One such a user scenario could i.e. be:

Currently, querying ArangoDB with GraphQL requires building a GraphQL.js schema. This is tedious and the resulting JavaScript schema file can be long and bulky. Here we will demonstrate a short proof of concept that reduces the user related part to only defining the GraphQL IDL file and simple AQL queries.

The Apollo GraphQL project built a library that takes a GraphQL IDL and resolver functions to build a GraphQL.js schema. Resolve functions are called by GraphQL to get the actual data from the database. I modified the library in the way that before the resolvers are added, I read the IDL..

Following the previous blog post on performance analysis with pyArango, where we had a look at graphing using statsd for simple queries, we will now dig deeper into inspecting transactions. At first, we split the initialization code and the test code.