Exploring Cloud Opportunities from an Array Database Perspective

Dumitru, Alex Mircea; Merticariu, Vlad; Baumann, Peter

doi:10.1145/2627770.2627775

Cited by 28 publications

(11 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It extends SQL with support for massive multidimensional arrays, together with declarative array operators which are heavily optimized and parallelized (Dumitru et al 2014) on server side. A separate layer adds geo semantics, such as knowledge about regular and irregular grids and coordinates, by implementing the OGC Web service interfaces.…”

Section: Array Databases As Datacube Platformmentioning

confidence: 99%

See 1 more Smart Citation

Fostering Cross-Disciplinary Earth Science Through Datacube Analytics

Baumann

Rossi

Bell

et al. 2018

Earth Observation Open Science and Innovation

Self Cite

View full text Add to dashboard Cite

With the unprecedented increase of orbital sensor, in situ measurement, and simulation data there is a rich, yet not leveraged potential for obtaining insights from dissecting datasets and rejoining them with other datasets. Obviously, goal is to allow users to "ask any question, any time, on any size", thereby enabling them to "build their own product on the go".One of the most influential initiatives in EO is EarthServer which has demonstrated new directions for flexible, scalable EO services based on innovative NoSQL

show abstract

Section: Array Databases As Datacube Platformmentioning

confidence: 99%

“…This way, single queries have been successfully split across more than a thousand Amazon cloud nodes (Dumitru et al 2014). Figure 20 shows an experiment done on the rasdaman distributed query processing visualization workbench where nine Amazon nodes process a query on 1 TB processed in 212 ms.…”

Section: Array Processingmentioning

confidence: 99%

Fostering Cross-Disciplinary Earth Science Through Datacube Analytics

Baumann

Rossi

Bell

et al. 2018

Earth Observation Open Science and Innovation

Self Cite

View full text Add to dashboard Cite

show abstract

“…Single queries have successfully been split across more than 1,000 cloud nodes [15]. Figure 7 shows the overall system architecture of rasdaman.…”

Section: Methodsmentioning

confidence: 99%

Standards-Based Services for Big Spatio-Temporal Data

Baumann¹,

Merticariu²,

Dumitru³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:With the unprecedented availability of continuously updated measured and generated data there is an immense potential for getting new and timely insights -yet, the value is not fully leveraged as of today. The quest is up for high-level service interfaces for dissecting datasets and rejoining them with other datasets -ultimately, to allow users to ask "any question, anytime, on any size" enabling them to "build their own product on the go". With OGC Coverages, a concrete, interoperable data model has been established which unifies n-D spatio-temporal regular and irregular grids, point clouds, and meshes. The Web Coverage Service (WCS) suite provides versatile streamlined coverage functionality ranging from simple access to flexible spatio-temporal analytics. Flexibility and scalability of the WCS suite has been demonstrated in practice through massive services run by large-scale data centers. We present the current status in OGC Coverage data and service models, contrast them to related work, and describe a scalable implementation based on the rasdaman array engine.

show abstract

“…Rasdaman databases of individual sizes exceeding 100 TB are up and running, and complex array queries have been distributed successfully across more than 1,000 cloud nodes [6].…”

Section: Methodsmentioning

confidence: 99%

Grooming big data from afar

Baumann

Dumitru

Merticariu

2015

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

Self Cite

View full text Add to dashboard Cite

Flexible, scalable services on massive geo data receive much attention today. In particular, the OGC Web Coverage Service (WCS) standards suite has established a best practice for versatile access and retrieval on spatio-temporal "Big Data". Fewer efforts have been devoted, though, to an easy-to-use, standardized way of maintaining a service's offering. Our experience from supporting a series of heterogeneous, large-scale services reveals that this can become tedious indeed, due to heterogeneity and incompleteness of incoming data, operator-less transformation and ingest of large amounts of files, as well as the need for narrowly focused manual corrections and updates sometimes.In this contribution, we present the WCS-T (for "Transaction") specification which enables users and machines to perform atomic insertion, updating, and deletions through simple Web requests. WCS-T has been implemented and is actively being used in projects; recently, it has entered the adoption process in OGC to become part of the WCS suite.

show abstract

Exploring Cloud Opportunities from an Array Database Perspective

Cited by 28 publications

References 12 publications

Fostering Cross-Disciplinary Earth Science Through Datacube Analytics

Fostering Cross-Disciplinary Earth Science Through Datacube Analytics

Standards-Based Services for Big Spatio-Temporal Data

Grooming big data from afar

Contact Info

Product

Resources

About