Skip to content

An empirical comparison of graph databases

In recent years, more and more companies provide services that can not be anymore achieved efficiently using relational databases. As such, these companies are forced to use alternative database models such as XML databases, object-oriented databases, document-oriented databases and, more recently graph databases. Graph databases only exist for a few years. Although there have been some comparison attempts, they are mostly focused on certain aspects only.
In this paper, we present a distributed graph database comparison framework and the results we obtained by comparing four important players in the graph databases market: Neo4j, OrientDB, Titan and DEX.

 

Salim Jouili, and Valentin Vansteenberghe, An empirical comparison of graph databases, proceedings of the 2013 ASE/IEEE International Conference on Big Data, Washington D.C., USA, September 2013.

Click here to access the paper.

Releated Posts

Investigating a Feature Unlearning Bias Mitigation Technique for Cancer-type Bias in AutoPet Dataset

We proposed a feature unlearning technique to reduce cancer-type bias, which improved segmentation accuracy while promoting fairness across sub-groups, even with limited data.
Read More

Muppet: A Modular and Constructive Decomposition for Perturbation-based Explanation Methods

The topic of explainable AI has recently received attention driven by a growing awareness of the need for transparent and accountable AI. In this paper, we propose a novel methodology to decompose any state-of-the-art perturbation-based explainability approach into four blocks. In addition, we provide Muppet: an open-source Python library for explainable AI.
Read More