ArangoDB’s outpost in the Bay area is getting more and more crowded. CTO Frank @fceller has joined the team of our CEO Claudius @weinberger, and ArangoDB´s lead developers: Max @neunhoef & Michael @mchacki. The latter are in San Francisco for a while already.
You can meet our team by attending several Meetups, the Collision Conf in Vegas (5-7 May) or at the @GeekdomSF office at Folsom Street #100, near Moscone Center. Get in touch, grab’ a coffee and join the discussions about NoSQL and multi-model databases. We are here to stay – at least until the end of May. (more…)
Waiting for a
git pull to complete over an 8 KiB/s internet connection is boring. So I thought I’d rather use the idle time and quickly write about some performance improvements for certain AQL functions that were recently completed and that will become available with ArangoDB 2.6.
The improvements affect the following AQL functions:
UNSET(): remove specified attributes from an object/document
KEEP(): keep only specified attributes of an object/document
MERGE(): merge the attributes of multiple objects/documents
This blog post shows a few example queries that will benefit from 50 to more than 60 % reductions in query execution times due to the changes done to these functions.
It is often difficult and time-consuming to setup a cluster environment for development or production purposes. For this reason, we decided to make an initial setup for you as easy as possible.
Today we’re introducing the first part of our new deployment tool for cloud computing platforms:
Part 1: Digital Ocean
We’ve released our first prototype, which deploys an ArangoDB Cluster on Digital Ocean. Just download a single bash script, export your Digital Ocean API Token and watch the tool take care of the rest for you.
chmod 755 DigitalOcean_ArangoDB_Cluster.sh
If you are interested in NoSQL and come from France, the NoSQL matters conference in Paris is your place to go. ArangoDB contributes with a workshop and a talk and is a silver sponsor of the conference as well. You can meet our team at the exhibition space and ask your ArangoDB questions in person.
Tickets are available for both days, starting at €299 for the conference pass.
For one lucky member of our community the conference could be for free – we have one ticket left for the conference day, March, 27th.
Join parts of the ArangoDB team in San Francisco. Max and Claudius are visiting the Bay Area from mid-February till end of March. Starting with the StrataConf in San Jose, Feb 17–20, 2015 Max and Claudius want to meet people, start cooperations, visit meetups and tell people in the Bay Area about ArangoDB.
If you know any hackerspaces we definitely should go, drop us a line and we will try to be there. We would be happy to see some of you guys in person and to respond to every question you may have about ArangoDB.
ArangoDB is multithreaded and able to use several CPU-cores at once. Because of that access to common data structures to these threads have to be protected from concurrent access. ArangoDB currently uses mutexes, spinlocks and RW-locks for that. With the ongoing development of the MVCC the number of situations where protected access is needed grows significantly. If locking is done too often the scalability is effectively limited to one core. So this test was done to estimate the costs, and evaluate other solutions – so called lockless programming with atomics.
We have moved our ArangoDB Github repository from triAGENS to arangodb.
triAGENS/ArangoDB –> arangodb/arangodb
We’ve also moved:
- arangodb-php –> arangodb/arangodb-php
- elasticsearch-river-arangodb –> arangodb/elasticsearch-river-arangodb
For a certain amount of time the old triAGENS – repositories will redirect to the new ones.
I have been looking at many AQL queries during the last few weeks…
Looking back, I can say that the JSON query execution plans provided by the
explain() method have provided me with a lot of useful information about how the AQL optimizer had transformed a given query. This has helped testing and improving the query optimizer a great deal.
However, the JSON output produced by
explain() is so detailed that even for the simplest cases queries it will span multiple screens. This is far too much for quickly assessing what a query will be doing and how it will be executed.
I therefore quickly put together a function that provides a much more compact explain output. Its input parameter is a query string, which it will send to the ArangoDB server to have it explained.
But it doesn’t print a voluminous JSON object. This one is for developers with a full schedule.
More than two years ago, we compared the bulk insert performance of ArangoDB, CouchDB and MongoDB in a blog post.
The original blog post dates back to the times of ArangoDB 1.1-alpha. We have been asked several times to re-run the tests with the current versions of the databases. So here we go.