Personne

Angelos Christos Anadiotis

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https://people.epfl.ch/angelos.anadiotis?lang=fr

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https://people.epfl.ch/angelos.anadiotis?lang=fr

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Cours enseignés par cette personne (2)

CS-460: Systems for data management and data science

This is a course for students who want to understand modern large-scale data analysis systems and database systems. The course covers fundamental principles for understanding and building systems for

CS-322: Introduction to database systems

This course provides a deep understanding of the concepts behind data management systems. It covers fundamental data management topics such as system architecture, data models, query processing and op

Publications associées (9)

Veuillez noter qu'il ne s'agit pas d'une liste complète des publications de cette personne. Elle inclut uniquement les travaux sémantiquement pertinents. Pour une liste complète, veuillez consulter Infoscience.

One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

Anastasia Ailamaki, Angelos Christos Anadiotis, Periklis Chrysogelos, Syed Mohammad Aunn Raza

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version o ...

ACM2023

Graph integration of structured, semistructured and unstructured data for data journalism

Angelos Christos Anadiotis, Jingmao You

Digital data is a gold mine for modern journalism. However, datasets which interest journalists are extremely heterogeneous, ranging from highly structured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists ...

PERGAMON-ELSEVIER SCIENCE LTD2022

A system design for elastically scaling transaction processing engines in virtualized servers

Anastasia Ailamaki, Hillel Avni, Raja Appuswamy, Angelos Christos Anadiotis

Online Transaction Processing (OLTP) deployments are migrating from on-premise to cloud settings in order to exploit the elasticity of cloud infrastructure which allows them to adapt to workload variations. However, cloud adaptation comes at the cost of re ...

ASSOC COMPUTING MACHINERY2020

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