#Arangodb arangodb 27.8m series windows

Other key features in ArangoDB 3.8 include: Additionally, ArangoDB 3.8 includes new ArangoSearch Geo functions which enable geo-spatial queries, such as contains, distance, in-range, and intersects, allowing the combination of full-text and geo search. This further rounds out ArangoDB’s functionality as a multi-model database, helping businesses eliminate the need for ‘yet another tool’ to perform analysis on their data.ĪrangoDB 3.8 also adds support in ArangoSearch for Geo-spatial queries with the introduction of two new Geo Analyzers, geojson and geopoint, which can break up GeoJSON and JSON objects into a set of indexable tokens for further use with ArangoSearch Geo functions. The AQL Analyzer serves as a data transformation tool, as it is capable of running an AQL query to perform data manipulation and / or filtering.

The pipeline Analyzer is designed for advanced text search and analytics, for example first normalizing text for case insensitive search followed by n-gram tokenization. The pipeline Analyzer allows multiple Analyzers to be ‘chained’ together, where the output of an Analyzer is passed to the next for further processing. New ArangoSearch Capabilities: AQL, Geo, and Composable Pipeline AnalyzersĪrangoDB 3.8 sees the addition of new Analyzers to ArangoSearch. When used in an Enterprise Edition deployment of ArangoDB, especially combined with features like SmartGraphs that optimize graph queries at scale, the power of weighted traversals is enhanced across sharded data. This enables queries such as calculating travel times between cities, helping to support use cases including turn-by-turn directions or mapping delivery routes. Weighted Traversals (optimized for ArangoDB Enterprise)ĪrangoDB 3.8 supports a new graph traversal type, ‘weighted’, which enumerates paths by increasing weights. By being able to query ‘moments in time’, window operations helps ArangoDB users perform time-series analytics over their data. Window operations power aggregations over related rows, producing a result for each query row.

“ArangoDB 3.8 is a particularly exciting step in this direction as it includes a number of features highly-requested by our community and customers.” “Enabling data analytics and storage at scale – especially centered around graph – is one of the central use cases for many of our open-source users and customers,” said Jörg Schad, PhD, CTO at ArangoDB. This advanced search functionality further rounds out the database’s aim to provide the flexibility and scalability developers need to bring solutions to market as simply and efficiently as possible.

ArangoDB 3.8 also introduces geo-spatial search, composable Analyzers, and computed fields for ArangoSearch, ArangoDB’s natively-integrated, full-text search and ranking engine.

#Arangodb arangodb 27.8m series windows

Key new features in ArangoDB 3.8 include window operations, allowing analytics for time-series or user-defined windows of data, as well as a new ‘weighted’ graph traversal. ArangoDB 3.8 adds a number of new features for analytics at scale, combining graph, full-text, and Geo analytics into a highly-scalable database. The research firm also predicts that graph technologies will be used in 80% of data and analytics innovations by 2025. ArangoDB 3.8 includes new graph query and search functionality, helping to meet increasing demand for businesses to perform graph-powered analytics at scale.Īccording to Gartner, graph adoption will double by 2022. SAN FRANCISCO, and COLONGE, Germany (PRWEB) July 29, 2021ĪrangoDB, the leading open source multi-model graph database, today announced the GA release of ArangoDB 3.8.