Step-by-step we are getting closer and closer to the official release of ArangoDB 3.5. First of all, we want to send a biiiiig “Thank You!” to all the testers so far and all your feedback! Super helpful for us!

This Release Candidate post is dedicated to the four new features of ArangoSearch which extend the capabilities and provide pretty huge performance improvements, especially for queries including search & sorting.

Probably the most interesting new thing you can do (and the most requested) is to configure analyzers and provide custom stopword-lists among other configuration options for..

After a lot of planning, coding and testing we can finally share the first Release Candidate of ArangoDB 3.5 with you today. You can get it on our Technical Preview Download page: Community & Enterprise.

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 version of ArangoDB out there, but this time it’s something special. This new release includes two huge features: a C++ based full-text search and ranking engine called ArangoSearch; and largely extended capabilities for geospatial queries by integrating Google™ S2..

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.

Download the technical preview package for your OS: RC1 3.4 Community and RC1 3.4 Enterprise.

The team implemented over 40 new features, improvements and optimizations. In this short post, we will highlight just a few of them. You can find a full list in the release notes and..

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.

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.

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 always want to become more productive and clicking through a graphical UI is not the best way. Furthermore, this procedure is almost impossible to use in an automated deployment process. That’s why we decided to develop a node-based CLI tool to manage Foxx services, called ..

For the upcoming ArangoDB 3.4 release we’ve implemented a set of information retrieval features exposed via new database object `View`. The `View` object is meant to be treated as another data source accessible via AQL and the concept itself is pretty similar to a classical “materialized” view in SQL.

While we are still working on completing the feature, you can already try our retrieval engine in the Milestone of the upcoming ArangoDB 3.4 released today. You can download and give it a spin here:

Milestone ArangoDB 3.4

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.

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.