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ArangoDB 3.4 GA
Full-text Search, GeoJSON, Streaming & More
The ability to see your data from various perspectives is the idea of a multi-model database. Having the freedom to combine these perspectives into a single query is the idea behind native multi-model in ArangoDB. Extending this freedom is the main thought behind the release of ArangoDB 3.4. We’re always excited to put a new…
RC1 ArangoDB 3.4 – What’s new?
For ArangoDB 3.4 we already added 100,000 lines of code, happily deleted 50,000 lines and changed over 13,000 files until today. We merged countless PRs, invested months of problem solving, hacking, testing, hacking and testing again and are super excited to share the feature complete RC1 of ArangoDB 3.4 with you today.
Gartner Report: Top-Rated Operational Database Management Systems
Firstly, a huge thank you to all our customers that took the time to review ArangoDB for the Gartner Peer Insights “Voice of the Customer”: Operational Database Management Systems Market report. Without your help and assistance, the continued improvements and enhancements we make to our software wouldn’t be possible.
Time traveling with graph databases
Graph databases are often used to analyze relations within highly interconnected datasets. Social networks, recommendation engines, corporate hierarchies, fraud detection or querying a bill of materials are common use cases. But these datasets change over time and you as a developer or data scientist may want to time travel and analyze these changes. While ArangoDB…
Speeding Up Dump Restore in ArangoDB: Enhanced Data Recovery
Many ArangoDB users rely on our `arangodump` and `arangorestore` tools as an integral part of their backup and recovery procedures. As such, we want to make the use of these tools, especially `arangodump`, as fast as possible. We’ve been working hard toward this goal in preparation for the upcoming 3.4 release. We’ve made a number…
Data retrieval performance optimizations in ArangoDB 3.3.9
Our recent release 3.3.9 includes several performance optimizations for data retrieval cases. Benefits can be expected for both storage engines, MMFiles and RocksDB, AQL batch lookup queries, and cluster AQL queries. MMFiles index batch lookups For the MMFiles engine, an optimization has been made for retrieving multiple documents from an index (hash index, skiplist index…
An implementation of phase-fair reader/writer locks
We were in search for some C++ reader/writer locks implementation that allows a thread to acquire a lock and then optionally pass it on to another thread. The C++11 and C++14 standard library lock implementations std::mutex and shared_mutex do not allow that (it would be undefined behaviour – by the way, it’s also undefined behaviour…
ArangoSearch architecture overview
In this article, we’re going to dive deeper into our recently released feature preview in Milestone ArangoDB 3.4 – ArangoSearch which provides a rich set of information retrieval capabilities. In particular, we’ll give you an idea of how our search engine works under the hood. Essentially ArangoSearch consists of 2 components: A search engine and…
Foxx CLI – Managing Microservices
Anyone who has ever worked with our JavaScript framework Foxx was faced at some point with the challenge to install its Foxx service in its current ArangoDB instance or to replace the installed service with local code changes. This is not a big deal and can easily be done through ArangoDB’s WebUI. However, we developers…
Static binaries for a C++ application
TL;DR; This describes how to generate a completely static binary for a complex C++ application which runs on all variants of Linux without any library dependency. ArangoDB is a multi-model database written in C++. It is a sizable application with an executable size of 38MB (stripped) and quite some library dependencies. We provide binary packages…