I am working on a data-science project related on social relationship mining and need to store data in some graph databases. Initially I chose Neo4j as the database. But it seams Neo4j doesn't scale well. The alternative I found out are Titan and oriebtDB. I have gone through this comparison on these three Databases, But I would like to get more details on these databases. So Could some one help me in choosing the best one. Mainly I would like to compare performance, scaling, on line documentation/tutorials available, Python library support, query language complexity and graph algorithm support of these databases. Also is there any other good database options ?

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    $\begingroup$ Also consider Graphlab (python based): graphlab.com/products/create/overview.html Here's a good blog post about it as well: bugra.github.io/work/notes/2014-04-06/… I can't help you with the Titan vs oriebtDB discussion though. Hopefully someone will chime in with that. $\endgroup$
    – nfmcclure
    Dec 18, 2014 at 18:03
  • $\begingroup$ Also possible to use Spark and GraphX $\endgroup$ Dec 20, 2014 at 21:00
  • $\begingroup$ This article shows some details on scalability, special advantage for Titan. groups.google.com/forum/#!topic/orient-database/CpPh42ukfH4 $\endgroup$
    – Henry H.
    Jan 12, 2015 at 10:31
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    $\begingroup$ No, it's not; GraphX is not a database. $\endgroup$
    – Emre
    Mar 14, 2015 at 4:59
  • $\begingroup$ Since this was couple of months back, I assume you made some progress. Why not add your own answer (here or elsewhere?) $\endgroup$
    – Jayan
    Jun 2, 2015 at 16:59

1 Answer 1


I think you might have to keep overall Data pipelines and Machine learning pipelines in mind. For which you need a robust framework to move data between table like and graph like storage apart from powerful distributed processing. From my understanding Spark GraphX is promising to build these pipelines. Joseph Gonzalez's (one of the creator of GraphLab from CMU) talk on GraphX on youtube is worth watching.


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