Skip to content 
ES6 Features in New V8 Upgrade | ArangoDB Blog
ArangoDB 2.6 uses V8 engine version 3.31.74.1 for running its own and all user-defined JavaScript code. In ArangoDB 2.7 (currently in development), we have upgraded V8 to version 4.3.61.
The new V8 version in ArangoDB 2.7 provides several additional ES6 Harmony features that can be used to improve JavaScript usability and code quality. This blog post showcases strong mode and rest parameters, and also shows how to activate TurboFan, V8’s new JIT compiler for JavaScript.
ArangoDB 2.7 is in development right now, but it can be tried today by compiling it from source.
Multi-Model Benchmark: Round 1 Results | ArangoDB Blog
It’s time for another update of my NoSQL performance blog series. This hopefully concludes the first part of this series with the initial databases ArangoDB, MongoDB, Neo4J and OrientDB and I can now start to check out other databases. I’m getting a lot of requests to test others as well and I’ll try to add them as soon as possible. Pull requests to my repository are also more than welcome. Remember it is all open-source.
The first set of benchmarks was started as a proof that multi-model can compete with specialized solutions and I started with the corresponding top dogs (Neo4J and MongoDB) for graphs and documents. After the first blog post, we were asked by the community to include OrientDB as the other multi-model database, too, which makes sense and therefore I expanded the initial lineup.
Concluding the tests did take a bit longer than expected, because vendors took up the challenge and improved their products with impressive results – as we asked them to do. Still, for each iteration we needed some time to run all tests, see below. However, on the upside, everyone can benefit from the improvements, which is an awesome by-product of the benchmark tests. (more…)
Data Modeling with Multi-Model Databases: ArangoDB Insights
Max published an article on O’Reilly Radar about the use case he presented on Strata+Hadoop World in London earlier this year.
Read how multi-model databases can be used in an aircraft fleet maintenance system by mixing different data models within the same data store. 
A query language like AQL can help to answer maintenance questions like:
- What are all the parts in a given component?
- Given a (broken) part, what is the smallest component of the aircraft that contains the part and for which there is a maintenance procedure?
- Which parts of this aircraft need maintenance next week?
Read on: O’Reilly Radar – Data modeling with multi-model databases
ArangoDB 2.6.2: Maintenance Release for Enhanced Stability
ArangoDB 2.6.2 maintenance release available – ArangoDB download
- fixed issue #1383: bindVars for HTTP API doesn’t work with empty string
- fixed handling of default values in Foxx manifest configurations
- fixed handling of optional parameters in Foxx manifest configurations
Read more about the new features in ArangoDB 2.6 in our What’s new article, the AQL 2.5 vs. 2.6 performance shootout or our latest performance comparison of multi-model and specialized DB’s (MongoDB, Neo4j).
The Great AQL Shootout: ArangoDB 2.5 vs 2.6 Comparison
For the ArangoDB 2.6 release from last week we’ve put some performance tests together. The tests will compare the AQL query execution times in 2.5 and 2.6.
The results look quite promising: 2.6 outperformed 2.5 for all tested queries, mostly by factors of 2 to 5. A few dedicated AQL features in the tests got boosted even more, resulting in query execution time reductions of 90 % and more. Finally, the tests also revealed a dedicated case for which 2.6 provides a several hundredfold speedup.
Also good news is that not a single of the test queries ran slower in 2.6 than in 2.5.
ArangoDB 2.6.1: Maintenance Release for Improved Stability
The first maintenance release for ArangoDB 2.6 is available for download. This maintenance release is only relevant for Mac, Windows and the Raspberry.
Version 2.6.1 (2015-06-24)
- Add missing swagger files to cmake build. fixes #1368
- fixed documentation errors
Dockerizing a Bloom-Based Nonces Service in 10 Minutes
In this article I want to explain how to setup a nonce-microservice using docker.
Nonce are one-time tokens that are used to ensure that an action can only be taken once. In a project, we needed to ensure that a pay button is only pressed once. Note that nonces are not used to sign requests or identify a user. This is a separate mechanism.
ArangoDB contains a nonce implementation which is a variation of Bloom-filters. It allows to store nearly unlimited nonces within a limited amount of memory. Nonce are allowed to age, that is after an hour they might expire. If there is sufficient interest, I will explain the algorithm implemented in a separate blog post.
Improving Databases: Open Source Competitive Benchmark
TL;DR: Our initial benchmark has raised a lot of interest. Initially we wanted to show that multi-model can compete with other solutions. Due to the open and competitive way we have conducted the benchmark, the discussions around it have lead to improvements in all products, better algorithms, faster drivers and better ways to use the databases.
General Setup
From the outset we published all code and data and asked the vendors of all tested products as well as the general public, not only to run the tests on their own machines, but also to suggest improvements in the data models, test code, database configuration, driver usage and server configuration. This lead to a lively discussion, lots of pull requests and even to the release of improved versions of the database products themselves!
This process exceeded all our expectations and is yet another great example of community collaboration not only for fact finding but also for product improvements. Obviously, the same benchmark code will always show slightly different results when run on different hardware, operating systems, network setups and with more or less RAM. Therefore, a reliable result of a benchmark can essentially only be achieved by allowing everybody to run it on their own machines.
The technical setup is described in the above blog post. Let me briefly repeat the key facts.