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ArangoDB 2.5.2 Release: Enhanced Features & Stability

This version is deprecated. Download the new version of ArangoDB

A maintenance release of ArangoDB 2.5 is available for download. The latest v2.5.2 comes with cluster speedups, some fixes in cluster mode and improved graph queries.

You can start an ArangoDB cluster on Digital Ocean with a single command, other cloud services will follow in the next days. Please try the new release, maybe on Digital Ocean with the new cluster setup script, and provide us your feedback.

Which cloud provider should we support next?

Here are the changes in the current maintenance release:

v2_5_2 (Release notes)

  • modules stored in _modules are automatically flushed when changed
  • added missing query-id parameter in documentation of HTTP DELETE /_api/query endpoint
  • added iterator for edge index in AQL queries this change may lead to less edges being read when used together with a LIMIT clause
  • make graph viewer in web interface issue less expensive queries for determining a random vertex from the graph, and for determining vertex attributes
  • issue #1285: syntax error, unexpected $undefined near ‘@_to RETURN obj this allows AQL bind parameter names to also start with underscores
  • moved /_api/query to C++
  • issue #1289: Foxx models created from database documents expose an internal method
  • added Foxx.Repository#exists
  • parallelise initialization of V8 context in multiple threads
  • fixed a possible crash when the debug-level was TRACE
  • cluster: do not initialize statistics collection on each coordinator, this fixes a race condition at startup
  • cluster: fix a startup race w.r.t. the _configuration collection
  • search for db:// JavaScript modules only after all local files have been considered, this speeds up the require command in a cluster considerably
  • general cluster speedup in certain areas

Ingo Friepoertner

Ingo is dealing with all the good ideas from the ArangoDB community, customers and industry experts to improve the value provided by the company’s native multi-model approach. In former positions he worked as a product owner and tech consultant, building custom software solutions for large companies in various industries. Ingo holds a diploma in business informatics from FHDW University of Applied Sciences.

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