Sparksee (graph database): Difference between revisions
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| operating system = [[Cross-platform]] |
| operating system = [[Cross-platform]] |
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| genre = [[Graph Database]] |
| genre = [[Graph Database]] |
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| status = Active |
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| license = Dual-licensed: personal evaluation use / commercial use |
| license = Dual-licensed: personal evaluation use / commercial use |
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| website = [http://www.sparsity-technologies.com/#sparksee Sparsity-Technologies:Sparksee] |
| website = [http://www.sparsity-technologies.com/#sparksee Sparsity-Technologies:Sparksee] |
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Revision as of 11:15, 29 April 2021
| Developer(s) | Sparsity Technologies |
|---|---|
| Initial release | 2008 |
| Stable release | v5.2
/ 2015 |
| Operating system | Cross-platform |
| Type | Graph Database |
| License | Dual-licensed: personal evaluation use / commercial use |
| Website | Sparsity-Technologies:Sparksee |
Sparksee (formerly known as DEX) is a high-performance and scalable graph database management system written in C++.
Its development started in 2006 and its first version was available on Q3 - 2008. The fourth version is available since Q3-2010. There is a free community version, for academic or evaluation purposes, available to download, limited to 1 million nodes, no limit on edges.
Sparksee is a product originated by the research carried out at DAMA-UPC (Data Management group at the Polytechnic University of Catalonia). In March 2010 a spin-off called Sparsity-Technologies has been created at the UPC to commercialize and give services to the technologies developed at DAMA-UPC.
DEX changed name to Sparksee on its 5th release in February 2014.
Graph Model [1]
Sparksee is based on a graph database model,[2] that is basically characterized by three properties: data structures are graphs or any other structure similar to a graph; data manipulation and queries are based on graph-oriented operations; and there are data constraints to guarantee the integrity of the data and its relationships.
A Sparksee graph is a Labeled Directed Attributed Multigraph. Labeled because nodes and edges in a graph belong to types. Directed because it supports directed edges as well as undirected. Attributed because both nodes and edges may have attributes and Multigraph meaning that there may be multiple edges between the same nodes even if they are from the same edge type.
One of its main characteristics is its performance storage and retrieval for large graphs (in the order of billions of nodes, edges and attributes) implemented with specialized structures.
Technical Details
- Programming Language: C++
- API: Java, .NET, C++, Python, Objective-C
- OS Compatibility: Windows, Linux, Mac OS, iOS, BB10
- Persistency: Disk
- Transactions: full ACID
- Recovery Manager
See also
References
- ^ Martínez-Bazan, N., Muntés-Mulero, V., Gómez-Villamor, S., Nin, J., Sánchez-Martínez, M., and Larriba-Pey, J. 2007. Dex: high-performance exploration on large graphs for information retrieval. In Proceedings of the Sixteenth ACM Conference on Conference on information and Knowledge Management (Lisbon, Portugal, November 06–10, 2007). CIKM '07. ACM, New York, NY, 573-582.
- ^ R. Angles and C. Gutierrez. Survey of graph database models. Technical Report TR/DCC-2005-10, Computer Science Department, Universidad de Chile, October 2005.
Also
- D. Domínguez-Sal, P. Urbón-Bayes, A.Giménez-Vañó, S. Gómez-Villamor, N.Martínez-Bazán, J.L. Larriba-Pey. Survey of Graph Database Performance on the HPC Scalable Graph Analysis Benchmark. International Workshop on Graph Databases. July 2010.