Frameworks comparison

Name	Pregel[1]	Distributed GraphLab[2]	PowerGraph[3]	Restreaming Partitioning[8]	X-stream[4]	Fennel[5]	S-Powergraph[6]	Linear Embedding[7]
year	2010	2011	2012	2013	2013	2014	2015	2016
Bounded/Unbounded	Bounded	Bounded	Bounded	Bounded	Bounded	Unbounded	Unbounded	Unbounded
Dynamic state changes?	Yes, Edges and topology changes	Yes	Yes	Yes	No, Only the data stored in a vertices changes	Yes	Yes	Yes
vertex-cut/edge-cut	edge-cut	edge-cut	vertex-cut	edge-cut	edge-cut	edge-cut	vertex-cut	edge-cut
Considering power-law distribution?	No	Tests with natural graphs	Yes	Yes( Social graphs )	No	Tests with natural graphs	Yes	Tests with natural graphs
Considering other natural graph models?	No	No	No	Yes( web graphs )	No	No	No	No
Stream partitioning?	No	No	No	Yes	Yes, edges	Yes	Yes	Yes
Comments	Partitioning depends on used hash function	When the same graph ( or approx. ) repeatedly streamed	Partitions the vertices, then streaming edges from storage

###References

[1] Malewicz, G., Austern, M. H., Bik, A. J. ., Dehnert, J. C., Horn, I., Leiser, N., & Czajkowski, G. (2010). Pregel: a system for large-scale graph processing. Proceedings of the 2010 International Conference on Management of Data - SIGMOD ’10, 135–146. http://doi.org/10.1145/1807167.1807184

[2] Low, Y., Gonzalez, J., Kyrola, A., Bickson, D., & Guestrin, C. (2011). Distributed GraphLab: A Distributed Framework for Machine Learning in the Cloud, 716–727. http://doi.org/10.14778/2212351.2212354

[3] Gonzalez, J., Low, Y., & Gu, H. (2012). Powergraph: Distributed graph-parallel computation on natural graphs. OSDI’12 Proceedings of the 10th USENIX Conference on Operating Systems Design and Implementation, 17–30. Retrieved from https://www.usenix.org/system/files/conference/osdi12/osdi12-final-167.pdf

[4] Roy, A., Mihailovic, I., & Zwaenepoel, W. (2013). X-stream: edge-centric graph processing using streaming partitions. The Twenty-Fourth ACM Symposium on Operating Systems Principles, 472 – 488. http://doi.org/10.1145/2517349.2522740

[5] Tsourakakis, C., Gkantsidis, C., Radunovic, B., & Vojnovic, M. (2014). Fennel: Streaming graph partitioning for massive scale graphs. Proceedings of the 7th ACM International Conference on Web Search and Data Mining, 333–342. http://doi.org/10.1145/2556195.2556213

[6] Xie, C., Li, W.-J., & Zhang, Z. (2015). S-PowerGraph: Streaming Graph Partitioning for Natural Graphs by Vertex-Cut. Retrieved from http://arxiv.org/abs/1511.02586

[7] Aydin, K., Bateni, M., & Mirrokni, V. (2016). Distributed Balanced Partitioning via Linear Embedding, 387–396. http://doi.org/10.1145/2835776.2835829