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ArangoDB 3.3: DC2DC Replication, Encrypted Backup
Just in time for the holidays we have a nice present for you all – ArangoDB 3.3. This release focuses on replication, resilience, stability and thus on general readiness for your production small and very large use cases. There are improvements for the community as well as for the Enterprise Edition. We sincerely hope to have found the right balance between them. Read more
Spring is coming! – ArangoDB meets Spring Data
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!
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ArangoDB Java Driver: Load Balancing for Performance
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. Read more
ArangoDB Named Best Free Graph Database by G2 Crowd Users
ArangoDB named by G2 Crowd users as the most popular graph database used today.
ArangoDB has been identified as the highest rated graph database, based on its high levels of customer satisfaction and likeliness to recommend ratings from real G2 Crowd users.
ArangoDB received a near perfect 4.9 out of 5 star average for user satisfaction for its free platform across its 24 user reviews. ArangoDB users point to the database’s query language, availability and storage as the three most liked features of the product. Read more
AWS Neptune: A New Vertex in the Graph World — But Where’s the Edge?
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. Read More
ArangoDB | RocksDB Integration: Performance Enhancement
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 server with 24 logical CPU cores, 144GB ram, and two FusionIO flash PCI devices. Each FusionIO device cost about $10,000 at the time of the post. So RocksDB is naturally tuned for extremely fast and expensive systems. Here is an example Arangodb import on a machine similar to the RocksDB performance tester: Read more
ArangoDB | Introduction to Fuerte: ArangoDB C++ Driver
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 follow the instructions provided in the drivers README.md. Read More
ArangoDB 3.3 Beta Release – New Features and Enhancements
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.
This beta release is feature complete and contains stability improvements with regards to the recent milestone 1 and 2 of ArangoDB 3.3. However, it is not meant for production use, yet. We will provide ArangoDB 3.3 GA after extensive internal and external testing of this beta release. Read More
ArangoDB | Infocamere Investigation: Graph Databases Case Study
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 entrusted to serve and promote Italian businesses through over 300 branch offices located throughout the country. InfoCamere helps them in pursuing their goals in the interest of the business community. On behalf of the Chambers’ System, InfoCamere plays a key-role in implementing the Italian Digital Agenda with respect to the digital transformation process of the national productive system, especially focusing on supporting the digitalization of SMEs.
Guest post by Luca Sinico (Software Developer, InfoCamere)
Performance analysis with pyArango: Part III Measuring possible capacity with usage Scenarios
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. Read more
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