This year we got a lot of requests from our customers to provide Spring Data support for ArangoDB. So we listened and teamed up with one of our bigger customers from the financial sector to develop a Spring Data implementation for ArangoDB. We have also made an extensive demo on how to use Spring Data ArangoDB with an example data set of Game of Thrones characters and locations. So, Spring is not only coming… it is already there!
Estimated reading time: 2 minutes
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.
Estimated reading time: 1 minutes
ArangoDB named by G2 Crowd users as the most popular graph database used today.
Estimated reading time: 8 minutes
At AWS Re:Invent just a few days ago, Andy Jassy, the CEO of AWS, unveiled their newest database product offerings: AWS Neptune. It’s a fully managed, graph database which is capable of storing RDF and property graphs. It allows developers access to data via SPARQL or java-based TinkerPop Gremlin. As versatile and as good as this may sound, one has to wonder if another graph database will solve a key problem in modern application development and give Amazon an edge over its competition.
Estimated reading time: 4 minutes
I have varying levels of familiarity with Google’s original leveldb and three of its derivatives. RocksDB is one of the three. In each of the four leveldb offerings, the code is optimized for a given environment. Google’s leveldb is optimized for a cell phone, which has much more limited resources than a server. RocksDB is optimized for flash arrays on a large servers (per various Rocksdb wiki pages). Note that a flash array is a device of much higher throughput than a SATA or SSD drive or array. It is a device that sits on the processor’s bus. RocksDB’s performance benchmark page details a..
Estimated reading time: 5 minutes
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..
Estimated reading time: 1 minutes
It is all about improving replication. ArangoDB 3.3 comes with two new exciting features: data-center to data-center replication for clusters and a much improved active-passive mode for single-servers. ArangoDB 3.3 focuses on replications and improvements in this area and provides a much better user-experience when setting up a resilient single-servers with automatic failover.
Estimated reading time: 5 minutes
InfoCamere is the IT company of the Italian Chambers of Commerce. By devising and developing up-to-date and innovative IT solutions and services, it connects the Chambers of Commerce and their databases through a network that is also accessible to the public via the Internet. Thanks to InfoCamere, businesses, Public Authorities, trade associations, professional bodies and simple citizens – both in Italy and abroad – can easily access updated and official information and economic data on all businesses registered and operating in Italy.
The Italian Chambers of Commerce are public bodies..
Estimated reading time: 14 minutes
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:
Estimated reading time: 3 minutes
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..
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