![]() ![]() For simple persistence and to show the entity relationship for a simple graphical display representation use standalone neo4j. neo4j specifications: 24G 24G 8G neo4j version: Community 4.2.0 desktop version: 1.3. For real time processing and processing large data-sets, use neo4j with GraphX. UserIndex.get( "name", name ). Conclusion: It is always recommended to use the Hybrid combination of Neo4j with GraphX as they both easier to integrate. Public Iterator getFriends( String name ) Public FriendOfAFriendDepth4( GraphDatabaseService db ) evaluator( new Evaluation evaluate( Path path ) relationships( withName( "FRIEND" ), Direction.OUTGOING ) Private static final TraversalDescription traversalDescription = However, on a MacBook Air (1.8 GHz i7, 4 GB RAM) with a 2 GB heap, GCR cache, but no warming of caches, and no other tuning, with a similarly sized dataset (1 million users, 50 friends per person), I repeatedly get approx 900 ms using the Traversal Framework on 1.9.2: public class FriendOfAFriendDepth4 I'm sorry you can't reproduce the results. Is there anything I can do to speed neo4j up (to be faster then mysql)?Īnd also there is another benchmark in Stackoverflow with same problem. ![]() My query to neo4j looks like this (using the REST api): start person=node:node_auto_index(noscenda_name="person123") match (person)->()->(friend) return count(distinct friend) Using 1.9.2 on a 64bit ubuntu I have setup neo4j.properties with these values: .mapped_memory=250M "*": single run only My results for 1 million people Short version: while trying to verify the performance claims made in the 'Graph Database' book I came to the following results (querying a random dataset containing n people, with 50 friends each): My results for 100k people The whole story (including scripts etc) is on I have updated the setup and tests, and don't want to change the original question too much. If you're already familiar with Cassandra, that helps quite a bit around the architecture side.This is a follow up to can't reproduce/verify the performance claims in graph databases and neo4j in action books. As such, you may have to rethink schema design as well as application code design. That being said, I will be upfront with you, Neo4J and DSE Graph are very different systems. I suggest reaching out to DataStax directly for those questions, they'll be happy to help. There's a lot to your question, especially around design, that can't be accurately answered in a StackOverflow post since a lot of it is specific to your use case. That looks something like graph.io(yo()).writeGraph("tinkerpop-modern.kryo") You can essentially connect to your Neo4J instance via the gremlin console, get the data you'd like, and write it out to a file that can be loaded into DSE Graph. We need to determine the level of effort would involved to do this exercise before we could be up and running on DataStax DSE Graph. ![]() We would like to see what it takes to migrate our existing Neo4J Java code to DataStax DSE Graph code. Does DataStax DSE Graph support something similar to plugins and/or unmanaged Extensions? Our business logic code in Java gets called whenever Neo4J searches/traverses graph database. We have developed some Plugins/Unmanaged Extensions in Neo4J using Java which have lots of core business rules incorporated into Neo4J. ![]()
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