Posted on 2018-11-30 by Bitnine Global

The AgensGraph Development Team are pleased to announce the release of AgensGraph v2.0.

AgensGraph is a new generation multi-model graph database for PostgreSQL. AgensGraph offers the graph analysis environment for highly connected data in which users can write, edit, and execute SQL and Cypher query together at the same time. AgensGraph comes along with PostgreSQL compatibility and PostgreSQL Extensions. It is why AgensGraph can set PostgreSQL users free from the pains of data migration and enables an easier development of graph-based applications than other graph databases.

This release of AgensGraph v2.0 includes many updates in PG compatibility, usability and performance with known bug fixes. For more details please see the release notes.

Major Improvements and Bug Fixes:
  • PostgreSQL Compatibility
  • Support PostgreSQL 10.4
  • Performance
  • Remove use of SPI in ModifyGraph
  • Cypher Implementation
  • Support STARTS WITH / ENDS WITH / CONTAINS clauses
  • Support PREPARE statement for Cypher
  • Usability
  • Support ‘=~’ operator for regex matching
  • Support ‘graphid’ comparisons
    ex) MATCH (n) WHERE id(n) = ‘1.1’ AND id(n) = 1.1 RETURN n;
  • Support implicit conversion of any value to jsonb during LOAD
    ex) LOAD FROM external_table AS r CREATE (:v = r);
  • Support printing NULL values in _vertex, _edge, and graphpath
  • Validate AG_VERSION before init or start
  • Added installation step for RHEL
  • Addition of the metric catalog ag_graphmeta
  • Improved labels() on vertex
  • Support storing NULL properties
  • Support DROP VLABEL … CASCADE
  • Bug Fixes
  • Bug fixes related to Cypher, graphpath, graph joins, etc.
    (Please see the release notes for fix details)
The new version is immediately available for download.

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Posted on 2018-11-30 by Bitnine Global The AgensGraph Development Team are pleased to announce the release of AgensGraph v2.0. AgensGraph is a new generation multi-model graph database for PostgreSQL. AgensGraph offers the graph analysis environment for highly connected data in which...

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