Graph Database Performance Comparison: Neo4j vs NebulaGraph vs JanusGraph

Performance Comparison: Neo4j vs NebulaGraph vs JanusGraph

Who Did the Graph Database Comparison

This article describes how the Tencent Cloud team compares NebulaGraph 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. 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.

NebulaGraph

NebulaGraph 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(R) Gold 6133 CPU @ 2.5GHz X86_64
# of Physical CPUs	2
# of Physical Cores	20
# of Logical CPUs	80
Memory	260 GB

Graph Database Performance Comparison 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
	NebulaGraph	32.63s	1.482ms	3.095ms	0.994ms
100 Million Edges	Neo4j	1min21s	42.921s	43.332s	44.072s
	HugeGraph	10min	19ms	20ms	5s
	NebulaGraph	3min52s	1.971ms	4.34ms	4.147ms
1 Billion Edges	Neo4j	8min34s	165.397s	176.272s	168.256s
	HugeGraph	65min	19ms	651ms	3.8s
	NebulaGraph	29min35s	2.035ms	22.48ms	1.761ms
8 Billion Edges	Neo4j	1h23min	314.34s	393.18s	608.27s
	HugeGraph	16h	68ms	24s	541ms
	NebulaGraph	~30min	Less than 1s	Less than 5s	Less than 1s

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

Here is a chart overview of the comparison:

Graph Database Performance Comparison Chart

Graph Query Language Comparison

Neo4j Cypher

One-Hop Friends Query

match ({vid:11111}) -> (u)
return u;

Two-Hop Friends Query

match ({vid:11111}) -> () -> u
return u;

Shared Friends Query

match ({vid:11111}) -> (u) <- ({vid:22222})
return u;

NebulaGraph nGQL