ArangoDB 3.4 has been released today. Major new enhancements include ArangoSearch, a feature which transforms ArangoDB, when combined with traversals or joins in AQL, from a data retrieval to an information retrieval solution. It also comes with full GeoJSON Support enabled by a Google S2 Geo Index library integration.
This new feature provides a rich set of information retrieval capabilities. It consists of two components – a search engine and an integration layer.
ArangoSearch can be combined with all three data models in ArangoDB. It uses materialized view to enable full-text search on multiple collections at once.
Users can now perform relevance-based matching, phrase and prefix matching, search with complex Boolean expressions, query time relevance tuning and combine complex traversals, geo-queries, and other access patterns with information retrieval techniques.
GeoJSON is an open standard format designed for representing simple geographical features, along with their non-spatial attributes.
ArangoDB comes with full support of all geo primitives, including multi-polygons or multi-line strings. It also includes a Google S2 Geometry Library integration which complements ArangoDB’s RocksDB storage engine. Users can also directly visualize results in OpenStreetMap which is integrated into the Query Editor of ArangoDBs WebUI.
The full list of features is available in ArangoDB release notes.
Introducing TigerGraph Cloud: A database as a service in the Cloud with AI and Machine Learning support
RedisGraph v1.0 released, benchmarking proves its 6-600 times faster than existing graph databases.
Introducing EuclidesDB, a multi-model machine learning feature database.