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Milestone ArangoDB 3.4: ArangoSearch – Information retrieval with ArangoDB

Estimated reading time: 7 minutes

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

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An Introduction to Geo Indexes and their performance characteristics: Part II

Estimated reading time: 5 minutes

Geo Index Implementation

This section will cover the MMFiles based geo-index. The algorithm is optimized for in-memory accesses and optimal CPU cache utilization. The main goal for our geo queries is to reject as many distant possible result points as fast as possible.

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ArangoJS 6.0.0 released: Load Balancing, Automated Failover and completely written in TypeScript

Estimated reading time: 2 minutes

Version 6.0.0 of the JavaScript driver arangojs is now available (Find it on GitHub).

This is a major release that introduces a small number of breaking changes so make sure to check out the arangojs changelog before upgrading. The most significant additions in this release are support for load balancing and automated failover as well as improved browser and TypeScript support.

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Present and Future of ArangoDB Fulltext Index

Estimated reading time: 2 minutes

The ArangoDB Fulltext index allows you to search for text in arbitrary strings. It is a great way to implement things like autocompletion, product searches or many other use-cases which need some form of fulltext search.The Fulltext Index is suitable for you if your use-case can be broken down to:

  • Full matches of words
  • Prefix matches of words
  • You do not need a “ranking” of the matching documents
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An Introduction to Geo Indexes and their performance characteristics: Part I

Estimated reading time: 8 minutes

Starting with the mass-market availability of smartphones and continuing with IoT devices, self-driving cars ever more data is generated with geo information attached to it. Analyzing this data in real-time requires the use of clever indexing data-structures. Geo data in ArangoDB consists of 2 or more dimensions representing (x, y) coordinates on the earth surface. Searching on a single number is essentially a solved problem, but effectively searching on multi-dimensional data can be more difficult as standard indexing techniques cannot be used.There exist a variety of indexing techniques. In..

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ArangoDB 3.3 GA DC2DC Replication, Encrypted backup, Server-Level Replication and more

Estimated reading time: 6 minutes

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.

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Spring is coming! – ArangoDB meets Spring Data

Estimated reading time: 3 minutes

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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Introducing the new ArangoDB Java driver with load balancing and advanced fallback

Estimated reading time: 2 minutes

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.

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ArangoDB Named Best Free Graph Database by G2 Crowd Users

Estimated reading time: 1 minutes

ArangoDB named by G2 Crowd users as the most popular graph database used today.

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AWS Neptune: A New Vertex in the Graph World — But Where’s the Edge?

Estimated reading time: 8 minutes

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.

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