Module: Exareme

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Exareme aims to address the efficiency challenges encountered when running analytical queries upon vast amount of data of different nature (temporal or not) and distributed over hetereogenous sources.

To maximize the tree execution plan advantages Exareme uses an engine for analytical query processing and a suite of specialized techniques like extending the SQL language with user-defined functions (UDFs) enabling parallelism and data pipelines.

This allows keeping fast reponse time, adjusting the right resources according to needs and costs which in turns maximize the “value for money”.


See Exareme federation.


A Relational Approach to Complex Dataflows

Optimize ressource utilization and cost upon execution of analytical queries on large datasets. 

Exareme IaaS clouds in Optique

How Exareme optimizes Time/Cost querying.

Exareme in a nutshell

This slideshow with voice over shows the capabilities of Exareme regarding optimization including query distribution and parallelism. It also describes the components in use and their role in the architecture. Examples at the end of the slideshow illustrates some of the usages of Exareme.

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