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Performance Comparison: Neo4j vs Nebula Graph vs JanusGraph

Performance Comparison: Neo4j vs Nebula Graph vs JanusGraph

See a performance comparison between Neo4j, Nebula graph, and JanusGraph.

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Hangyu Li

Sep. 18, 20 · Review

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This article describes how the Tencent (HKG.0700) Cloud team compares Nebula Graph with two other popular graph databases on the market from several perspectives.

By their nature of dealing with interconnections, graph databases are perfect for fraud detection and building knowledge graphs in the security field. To better serve the Tencent Cloud business scenarios, the Tencent Cloud Security team has to select a highly performant graph database which fits the business development well, which is how this performance comparison comes into play.

Whom to Compare With

Neo4j

Neo4j is the most widely adopted graph database in the industrial world. It has a Community edition and an Enterprise edition. For comparison in this article, the team has chosen the Community edition.

HugeGraph (A fork of JanusGraph)

HugeGraph is a distributed graph database developed by Baidu (NASDAQ: BIDU). It is forked from JanusGraph. HugeGraph is developed to address the needs of anti-fraud, threat intelligence collection, and underground economy attack with graph storage and analysis capabilities. It has pretty good read and write performance.

Nebula Graph

Nebula Graph is an open source distributed graph database developed by vesoft inc. It features the capability of dealing with super large datasets with hundreds of billions of vertices and trillions of edges.

Hardware Environments

Item	Specs
CPU	Intel Xeon® Gold 6133 CPU @ 2.5GHz X86_64
# of Physical CPUs	2
# of Physical Cores	20
# of Logical CPUs	80
Memory	260 GB

Test Results

The Tencent Cloud Security team has used graph data at different orders of magnitudes for testing purpose. The test has been performed against various metrics, including data import efficiency, one-hop query, two-hop query, and shared friends query.

The results are as below:

Graph Data Size	Platform	Data Import	One-Hop Query	Two-Hop Query	Shared Friends Query
10 Million Edges	Neo4j	26s	6.618s	6.644s	6.661s
	HugeGraph	89s	16ms	22ms	72ms
	Nebula Graph	32.63s	1.482ms	3.095ms	0.994ms
100 Million Edges	Neo4j	1min21s	42.921s	43.332s	44.072s
	HugeGraph	10min	19ms	20ms	5s
	Nebula Graph	3min52s	1.971ms	4.34ms	4.147ms
1 Billion Edges	Neo4j	8min34s	165.397s	176.272s	168.256s
	HugeGraph	65min	19ms	651ms	3.8s
	Nebula Graph	29min35s	2.035s	22.48ms	1.761ms
8 Billion Edges	Neo4j	1h23min	314.34s	393.18s	608.27s
	HugeGraph	16h	68ms	24s	541ms
	Nebula Graph	~30min	Less than 1s	Less than 5s	Less than 1s

Seen from the above table, in terms of data import, Nebula Graph is a bit slower than Neo4j when the data size is small. However, when the data size is large, Nebula Graph is much faster than the other two. For the three graph queries, Nebula Graph shows clearly better performance compared to Neo4j and HugeGraph.

Here is a chart overview for the comparison:

👁 Image

Graph Query Language Comparison

Platform / Query Language	One-Hop Friends Query	Two-Hop Friends Query	Shared Friends Query
Neo4j / Cypher	match ( {vid:11111} ) -> (u) return u;	match ( {vid:11111} ) -> () -> u return u;	match ( {vid:11111} ) -> (u) <- ({vid:22222}) return u;
HugeGraph / gremlin	g.V ().has (‘vid’, ‘attr’, ‘11111’). both E ().otherV ().dedup ().count ()	g.V ().has (‘vid’, ‘attr’, ‘11111’). both E ().otherV ().dedup ().both E ().otherV ().count ()	g.V ().has (‘vid’, ‘attr’, ‘11111’). both E ().otherV ().aggregate(‘x’).has(‘vid’, ‘attr’, ‘22222’).bothE().otherV().where(within(‘x’)).dedup().count()
Nebula Graph / nGQL	GO FROM 11111 OVER relation	GO 2 STEPS FROM 11111 OVER relation	GO FROM 11111 OVER relation INTERSECT GO FROM 22222 OVER relation

From the graph query language point of view, gremlin is complex and nGQL and Cypher are simple and neat. From the readability point of view, nGQL is similar to SQL and the learning curve should be shorter.

Graph Visualization Comparison

Platform	Layout Support	Smoothness	Exploration from a Selected Node	Query in Batch	Node Style Customization
Neo4j	Yes	Smooth for one-hop query	No	Yes	Yes
HugeGraph	No	Smooth for one-hop query	No	No	Yes
Nebula Graph	Yes	Smooth for one-hop query	Yes	Yes	No

In terms of graph visualization, it is safe to say that all the mentioned platforms are just available for use. Nebula Graph supports exploration from a selected node, which is a plus. However, there is still room for improvement for the smoothness of two-hop friends query results layout and node style customization.

After comparing multiple widely adopted open source graph databases and taking into consideration of factors such as performance, learning curve, and fitness to the business scenarios, the Tencent Cloud Security team has finally selected Nebula Graph, a highly performant and easy-to-use graph database.

Graph (Unix) Database Nebula (computing) Neo4j Comparison (grammar)

Published at DZone with permission of Hangyu Li. See the original article here.

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