Released OrientDB 1.3 with new SQL functions and better performance

London, November, 21st 2012
NuvolaBase is glad to announce this new release 1.3 and the new Web Site of OrientDB:!

Sorry for the delay about this official email, but we did extra work after the switch from Google Code to GitHub. Thank you to all the contributors helped us in this migration, specially Adrian Madrid for the adapted WiKi pages. In the next days we’re going to improve the documentation by involving all the authors of Drivers to contribute with a short tutorial and a quick reference for the usage of the driver.

What’s new with 1.3?

  • SQL: new eval() function to execute expressions
  • SQL: new if() and ifnull() functions
  • SQL: supported server-side configuration for functions
  • SQL: new DELETE VERTEX and DELETE EDGE commands
  • SQL: execution of database functions from SQL commands
  • SQL: new create cluster command
  • Graph: bundled 2 algorithms: Dijkstra and ShortestPath between vertices
  • Performance: improved opening time when a connections is reused from pool
  • Performance: better management of indexes in ORDER BY
  • Schema: new API to handle custom fields
  • HTTP/REST: new support for fetch-plan and limit in “command”
  • Moved from Google Code to GitHub:
  • Many bugs fixed
Full list: Full list: 


To report an issue please follow the suggestions posted in the group, in particular attach the following information:
  • OrientDB version. Please don’t forget this! If it’s a SNAPSHOT please tell if it’s from SVN (revision number) or from MAVEN
  • Operative System
  • 32-bit or 64-bit
  • JVM version
  • RAM
  • Dump of configuration and profiler
To open a new issue:
Professional Services
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We built a new Partnership Agreement for companies interested to sell NuvolaBase or OrientDB services as “reseller” or “services partner”. Please contact to have more information about it.
The roadmap has been updated -> The next release will be the 1.4 planned for January 2013 and then the long awaited 2.0 with the new distributed architecture with auto-sharding and parallel queries.
Thanks to all the committers, the contributors and final users.

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