publication . Other literature type . Conference object . Article . 2014

A Column-Store Meets The Point Clouds

Oscar Martinez-Rubi;
Open Access
  • Published: 12 Jul 2014
  • Publisher: Zenodo
  • Country: Netherlands
Abstract
htmlabstractDealing with LIDAR data in the context of database management systems calls for a re-assessment of their functionality, performance, and storage/processing limitations. The territory for efficient and scalable processing of LIDAR repositories using GIS enabled database systems is still largely unexplored. Bringing together hard core database management experts and GIS application developers is a sine qua non to advance the state of the art. In particular to assess the relative merits of both traditional row-based database engines and the modern column-oriented database engines.
Subjects
ACM Computing Classification System: GeneralLiterature_MISCELLANEOUSInformationSystems_DATABASEMANAGEMENT
free text keywords: GIS, Database systems, MonetDB
Related Organizations
Download fromView all 6 versions
Zenodo
Other literature type . 2014
Provider: Datacite
ZENODO
Conference object . 2014
Provider: ZENODO
Repository CWI Amsterdam
Conference object . 2014
Provider: NARCIS
17 references, page 1 of 2

[1] http://www.asprs.org/a/society/committees/lidar/lidar_format.html.

[2] http://www.laszip.org/.

[3] https://github.com/pramsey/pointcloud.

[4] http://ahn.geodan.nl/ahn/.

[5] D. Abadi, S. Madden, and M. Ferreira. Integrating Compression and Execution in Column-oriented Database Systems. SIGMOD, 2006.

[6] D. Abadi, D. Myers, D. DeWitt, and S. Madden. Materialization Strategies in a Column-Oriented DBMS. In ICDE, 2007.

[7] D. J. Abadi, S. R. Madden, and N. Hachem. Column-stores vs. Row-stores: How Different Are They Really? SIGMOD, 2008.

[8] P. Boncz, S. Manegold, and M. Kersten. Optimizing main-Memory join on modern hardware. TKDE, 2002. [OpenAIRE]

[9] P. Boncz, M. Zukowski, and N. Nes. MonetDB/X100: Hyper-pipelining query execution. CIDR, 2005. [OpenAIRE]

[10] P. A. Boncz and M. L. Kersten. MIL Primitives for Querying a Fragmented World. The VLDB Journal, 1999. [OpenAIRE]

[11] D. DeWitt and J. Gray. Parallel Database Systems: The Future of High Performance Database Systems. CACM, 1992. [OpenAIRE]

[12] M. Ivanova, Y. Kargin, M. Kersten, S. Manegold, Y. Zhang, M. Datcu, and D. E. Molina. Data Vaults: A Database Welcome to Scientific File Repositories. SSDBM, 2013. [OpenAIRE]

[13] M. Ivanova, M. Kersten, N. Nes, and R. Goncalves. An architecture for recycling intermediates in a column-store. TODS, 2010.

[14] M. Kersten, Y. Zhang, M. Ivanova, and N. Nes. SciQL, a Query Language for Science Applications. AD, 2011.

[15] S. Manegold, M. Kersten, and P. Boncz. Database Architecture Evolution: Mammals Flourished Long Before Dinosaurs Became Extinct. VLDB, 2009. [OpenAIRE]

17 references, page 1 of 2
Abstract
htmlabstractDealing with LIDAR data in the context of database management systems calls for a re-assessment of their functionality, performance, and storage/processing limitations. The territory for efficient and scalable processing of LIDAR repositories using GIS enabled database systems is still largely unexplored. Bringing together hard core database management experts and GIS application developers is a sine qua non to advance the state of the art. In particular to assess the relative merits of both traditional row-based database engines and the modern column-oriented database engines.
Subjects
ACM Computing Classification System: GeneralLiterature_MISCELLANEOUSInformationSystems_DATABASEMANAGEMENT
free text keywords: GIS, Database systems, MonetDB
Related Organizations
Download fromView all 6 versions
Zenodo
Other literature type . 2014
Provider: Datacite
ZENODO
Conference object . 2014
Provider: ZENODO
Repository CWI Amsterdam
Conference object . 2014
Provider: NARCIS
17 references, page 1 of 2

[1] http://www.asprs.org/a/society/committees/lidar/lidar_format.html.

[2] http://www.laszip.org/.

[3] https://github.com/pramsey/pointcloud.

[4] http://ahn.geodan.nl/ahn/.

[5] D. Abadi, S. Madden, and M. Ferreira. Integrating Compression and Execution in Column-oriented Database Systems. SIGMOD, 2006.

[6] D. Abadi, D. Myers, D. DeWitt, and S. Madden. Materialization Strategies in a Column-Oriented DBMS. In ICDE, 2007.

[7] D. J. Abadi, S. R. Madden, and N. Hachem. Column-stores vs. Row-stores: How Different Are They Really? SIGMOD, 2008.

[8] P. Boncz, S. Manegold, and M. Kersten. Optimizing main-Memory join on modern hardware. TKDE, 2002. [OpenAIRE]

[9] P. Boncz, M. Zukowski, and N. Nes. MonetDB/X100: Hyper-pipelining query execution. CIDR, 2005. [OpenAIRE]

[10] P. A. Boncz and M. L. Kersten. MIL Primitives for Querying a Fragmented World. The VLDB Journal, 1999. [OpenAIRE]

[11] D. DeWitt and J. Gray. Parallel Database Systems: The Future of High Performance Database Systems. CACM, 1992. [OpenAIRE]

[12] M. Ivanova, Y. Kargin, M. Kersten, S. Manegold, Y. Zhang, M. Datcu, and D. E. Molina. Data Vaults: A Database Welcome to Scientific File Repositories. SSDBM, 2013. [OpenAIRE]

[13] M. Ivanova, M. Kersten, N. Nes, and R. Goncalves. An architecture for recycling intermediates in a column-store. TODS, 2010.

[14] M. Kersten, Y. Zhang, M. Ivanova, and N. Nes. SciQL, a Query Language for Science Applications. AD, 2011.

[15] S. Manegold, M. Kersten, and P. Boncz. Database Architecture Evolution: Mammals Flourished Long Before Dinosaurs Became Extinct. VLDB, 2009. [OpenAIRE]

17 references, page 1 of 2
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publication . Other literature type . Conference object . Article . 2014

A Column-Store Meets The Point Clouds

Oscar Martinez-Rubi;