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The purpose of workshops is to provide a more interactive and focused platform for presenting and discussing new and emerging ideas. The format of paper presentations may include oral presentations, poster presentations, keynote lectures and panels. Depending on the number of presentations, workshops can be scheduled for 1 day or 2 days. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), DBLP, EI (Elsevier Engineering Village Index) and Scopus.


ADITCA 20192nd Workshop on Appliances for Data-Intensive and Time Critical Applications
Chair(s): Marta Patiño-Martinez and Florent Masseglia

2nd Workshop on
Appliances for Data-Intensive and Time Critical Applications
 - ADITCA 2019

Paper Submission: May 28, 2019
Authors Notification: June 12, 2019
Camera Ready and Registration: June 21, 2019


Marta Patiño-Martinez
Universidad Politécnica de Madrid
Florent Masseglia

The current cloud landscape is getting populated with many applications that are being migrated to the cloud due to its convenience and ease of use. However, there are still a subset of applications that are not frequent in the cloud. These are data-intensive and time critical applications. Data intensive applications, in the best case, experience bad performance in the cloud as current cloud database infrastructure fails to satisfy high loads and does not provide predictable performance. Many critical applications run today on mainframes due to their high resilience and high performance. This workshop will be a dedicated forum to data-intensive and time critical applications and promising related research topics like, e.g., hardware enabling in-memory databases, in-memory scale-up operational databases, or high availability/efficiency.