Corpus ID: 204800872

Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries

@article{Besta2019DemystifyingGD,
  title={Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries},
  author={Maciej Besta and Emanuel K. Peter and Robert Gerstenberger and Marc Fischer and Michal Podstawski and Claude Barthels and Gustavo Alonso and Torsten Hoefler},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.09017}
}
Graph processing has become an important part of multiple areas of computer science, such as machine learning, computational sciences, medical applications, social network analysis, and many others. Numerous graphs such as web or social networks may contain up to trillions of edges. Often, these graphs are also dynamic (their structure changes over time) and have domain-specific rich data associated with vertices and edges. Graph database systems such as Neo4j enable storing, processing, and… Expand
Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems.
TLDR
This work provides the first analysis and taxonomy of dynamic and streaming graph processing, focusing on identifying the fundamental system designs and on understanding their support for concurrency, and for different graph updates as well as analytics workloads. Expand
Practice of Streaming and Dynamic Graphs: Concepts, Models, Systems, and Parallelism
TLDR
This work provides the first analysis and taxonomy of dynamic and streaming graph processing, focusing on identifying the fundamental system designs and on understanding their support for concurrency and parallelism, and for different graph updates as well as analytics workloads. Expand
A logical framework with a graph meta-language
TLDR
This work presents ongoing work on a logical framework with a meta-language based on graphs, including Fitch-style and backward-directed Natural Deduction systems for intuitionistic and classical logic, and a Hilbert-style system for the K modal logic. Expand
An overview of graph databases and their applications in the biomedical domain
TLDR
It is concluded that the available graph database management systems are fit to support data-intensive, integrative applications, targeted at both basic research and exploratory tasks closer to the clinic. Expand
Demystifying memory access patterns of FPGA-based graph processing accelerators
TLDR
This work builds on a simulation environment for graph processing accelerators, to make several existing accelerator approaches comparable and yields insights into the strengths and weaknesses of current graph processing Accelerators along these dimensions, and features a novel in-depth comparison. Expand
EIGA: elastic and scalable dynamic graph analysis
TLDR
This work presents ElGA, an elastic and scalable dynamic graph analysis system that outperforms state-of-the-art static systems while supporting client queries, elastic infrastructure changes, and dynamic algorithms. Expand
Enhanced adaptive partitioning in a distributed graph database
TLDR
A module is created for the graph computational framework TinkerPop that logs traffic generated by the user queries that yields a 70–80% improvement in intra-network communication, comparable to other methods, namely Ja-be-Ja, that offers similar results but has higher computational demands. Expand
Exploring Memory Access Patterns for Graph Processing Accelerators
TLDR
This work proposes a simulation environment for the analysis of graph processing accelerators based on simulating their memory access patterns and evaluates its approach on two state-of-the-art FPGAs to show reproducibility, comparablity, as well as the shortened development process by an example. Expand
GDBApex: A graph‐based system to enable efficient transformation of enterprise infrastructures
TLDR
The proposed graph‐based modeling approach uses a graph structure for semantic queries and applies software engineering design principles and outperformed relational database management systems by an order of magnitude. Expand
GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra
TLDR
GraphMineSuite (GMS) is proposed, the first benchmarking suite for graph mining that facilitates evaluating and constructing highperformance graph mining algorithms and is supported with a broad concurrency analysis for portability in performance insights, and a novel performance metric to assess the throughput of graphs mining algorithms. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 190 REFERENCES
Loading and Querying a Trillion RDF triples with Cray Graph Engine on the Cray XC
  • CUG,
  • 2018
Foundations of Modern Query Languages for Graph Databases
TLDR
The importance of formalisation for graph query languages is discussed, with a summary of what is known about SPARQL, Cypher, and Gremlin in terms of expressivity and complexity; and an outline of possible future directions for the area. Expand
An Experimental Comparison of Pregel-like Graph Processing Systems
TLDR
A study to experimentally compare Giraph, GPS, Mizan, and Graphlab on equal ground by considering graph and algorithm agnostic optimizations and by using several metrics finds that the system optimizations present in Giraph and GraphLab allow them to perform well. Expand
Efficient graph management based on bitmap indices
TLDR
The internals of DEX graph database is described, which is based on a representation of the graph and its attributes as maps and bitmap structures that can be loaded and unloaded efficiently from memory. Expand
The Object-Oriented Database System Manifesto
TLDR
This paper attempts to define an object-oriented database system and takes a position, not so much expecting it to be the final word as to erect a provisional landmark to orient further debate. Expand
A Survey on NoSQL Stores
TLDR
This survey mainly aims at elucidating the design decisions of NoSQL stores with regard to the four nonorthogonal design principles of distributed database systems: data model, consistency model, data partitioning, and the CAP theorem. Expand
Loading andQuerying a Trillion RDF triples with Cray Graph Engine on the Cray XC
  • Cray Users Group,
  • 2018
Querying Graphs
Semantics and Complexity of GraphQL
TLDR
This work proves that the complexity of the GraphQL evaluation problem is NL-complete, and shows that the enumeration problem can be solved with constant delay, and results on polynomial-time size computation plus the constant-delay enumeration can help developers to provide more robust GraphQL interfaces on the Web. Expand
RDF* and SPARQL*: An Alternative Approach to Annotate Statements in RDF
TLDR
The standard approach to annotate statements in RDF with metadata has a number of shortcomings including data size blow-up and complicated queries, so this work proposes an alternative approach that is based on knowledge representation. Expand
...
1
2
3
4
5
...