RC4 of ArangoDB 3.5: Configurable Analyzers & other ArangoSearch Upgrades

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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. Read more

RC2 ArangoDB 3.5: Data Masking & Time-to-Live Index

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Coding is finished. Tests are green. Today, we can share the second release candidate for ArangoDB 3.5. Get RC2 Community Edition or RC2 Enterprise Edition.

With this release candidate we want to highlight the next two features of the upcoming release. Data Masking and Time-To-Live indices (TTL) can come in very handy for developers when it comes to compliance with data privacy regulations like GDPR or the upcoming Consumer Privacy Act of California. Read more

ArangoDB 3.5 RC1: Graph Database Improvements with PRUNE & k Shortest Paths

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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: Tech Preview Community & Tech Preview Enterprise.

With this RC, we want to highlight two new features for all graph database enthusiasts: the new PRUNE Keyword & k Shortest Path Feature. As always, please note Release Candidates are for testing purposes only and should not be used in production. Please see limitations of RC1 at the bottom of the page! Read more

ArangoDB 3.4 GA
Full-text Search, GeoJSON, Streaming & More

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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 Geometry Library and GeoJSON.  Read more

RC1 ArangoDB 3.4 – What’s new?

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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. Read more

Data retrieval performance optimizations in ArangoDB 3.3.9

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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 or persistent index) in a batch.
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ArangoSearch architecture overview

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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 an integration layer. The former is responsible for managing the index, querying and scoring, whereas latter exposes search capabilities to the end user in a convenient way.

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