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Authors: Ricardo Jimenez 1 ; Marta Patino 2 ; Ivan Brondino 1 ; Valerio Vianello 2 ; Ricardo Vilaca 1 ; Boyan Kolev 3 ; Patrick Valduriez 3 ; Raquel Pau 4 ; Apostolos Hatzimanikatis 5 ; Vassilis Spitadakis 5 ; Dimitris Bouras 5 ; Yorgos Panagiotakis 5 ; Giorgos Saloustros 6 ; Anastasios Papagiannis 6 ; Pilar Gonzalez-Ferez 6 ; Angelos Bilas 6 ; Ying Zhang 7 ; Pavlos Kranas 8 ; Sotiris Stamokostas 8 ; Vrettos Moulos 8 ; Fotis Aisopos 8 ; Francois Sabary 9 ; Luis Cortesao 10 ; Diogo Regateiro 11 ; Jose Pereira 12 and Rui Oliveira 12

Affiliations: 1 LeanXcale, Spain ; 2 Universidad Politecnica de Madrid, Spain ; 3 INRIA, Missing City, France ; 4 Sparsity Technologies, Spain ; 5 Neurocom, Greece ; 6 Foundation for Research and Technology - Hellas (FORTH) & Institute of Computer Science (ICS), Greece ; 7 Xiamen University Tan Kah Kee College, China ; 8 National Technical University of Athens & ICCS, Greece ; 9 Quartet FS, France ; 10 Altice Labs, Portugal ; 11 Instituto de Telecomunicacoes, DETI, University of Aveiro, Portugal ; 12 INESC TEC, Portugal

Keyword(s): Polyglot Persistence, Transactions, ACID, Polyglot Queries, Query Processing, SQL, NoSQL, CEP, Big Data.

Abstract: There has been a blooming of new data stores addressing new challenges in data management of structured, semi-structured and unstructured data in the last years. In the semi-structured segment, many different kinds of NoSQL data stores have emerged proposing new data models and associated query languages and/or APIs appropriate for them, such as document-oriented data stores, key-value data stores and graph databases. On the structured data world, new technologies have emerged such as NewSQL, columnar data warehouses or inmemory databases. This adoption of new data stores store has led to a proliferation of data stores at organizations raising interesting challenges. On one hand, NoSQL data stores were born in a world where scalability was considered a key attribute and many of them attained this scalability by dismissing the transactional properties, since it was the main bottleneck in data management technology preventing from achieving scalability. This design decision has enabled many NoSQL data stores to achieve different degrees of scalability but at the cost of losing consistency in the advent of failures and/or concurrent access. On the other hand, having multiple data stores results in the so-called polyglot persistent environments that create two interesting problems. The first one happens when a business action requires updating data across multiple data stores, which lacks the transactional consistency provided by OLTP databases, resulting in a loss of consistency when conflicting accesses happen or a failure occurs at one or more nodes. The second one is that exploiting the data in a polyglot persistence environment is an extremely hard task unreachable for most organizations. The reason is that different data stores provide different query languages or APIs. This forces to program a query engine at the application level that is obviously not feasible for most organizations or to move all the data to a data warehouse forcing to put a relational schema to data that is schemaless such as the one stored on NoSQL data stores. It turns out that the motivation to introduce data stores is precisely to prevent to put under a relational schema data not suited for such model and requiring the flexibility of other data models such as documents, key-value or graphs. CoherentPaaS comes to solve the three above problems. On one hand, it solves the pains related to updates across different data sores by providing a holistic transactional manager that enriches NoSQL and other transaction-less data stores with transactional semantics without affecting their scalability and to execute holistic or global transactions across any subset of data stores integrated into the CoherentPaaS platform. On the other hand, it solves the problem related to queries in polyglot persistence environments by enabling the combination of SQL with the native query languages and naive APIs to make queries across data stores with arbitrary data models and their query processing framework. (More)

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Paper citation in several formats:
Jimenez, R.; Patino, M.; Brondino, I.; Vianello, V.; Vilaca, R.; Kolev, B.; Valduriez, P.; Pau, R.; Hatzimanikatis, A.; Spitadakis, V.; Bouras, D.; Panagiotakis, Y.; Saloustros, G.; Papagiannis, A.; Gonzalez-Ferez, P.; Bilas, A.; Zhang, Y.; Kranas, P.; Stamokostas, S.; Moulos, V.; Aisopos, F.; Sabary, F.; Cortesao, L.; Regateiro, D.; Pereira, J. and Oliveira, R. (2016). CoherentPaaS - A Coherent and Rich PaaS with a Common Programming Model. In European Space project on Smart Systems, Big Data, Future Internet - Towards Serving the Grand Societal Challenges - EPS Rome 2016; ISBN 978-989-758-207-3, SciTePress, pages 27-49. DOI: 10.5220/0007902800270049

@conference{eps rome 201616,
author={Ricardo Jimenez. and Marta Patino. and Ivan Brondino. and Valerio Vianello. and Ricardo Vilaca. and Boyan Kolev. and Patrick Valduriez. and Raquel Pau. and Apostolos Hatzimanikatis. and Vassilis Spitadakis. and Dimitris Bouras. and Yorgos Panagiotakis. and Giorgos Saloustros. and Anastasios Papagiannis. and Pilar Gonzalez{-}Ferez. and Angelos Bilas. and Ying Zhang. and Pavlos Kranas. and Sotiris Stamokostas. and Vrettos Moulos. and Fotis Aisopos. and Francois Sabary. and Luis Cortesao. and Diogo Regateiro. and Jose Pereira. and Rui Oliveira.},
title={CoherentPaaS - A Coherent and Rich PaaS with a Common Programming Model},
booktitle={European Space project on Smart Systems, Big Data, Future Internet - Towards Serving the Grand Societal Challenges - EPS Rome 2016},
year={2016},
pages={27-49},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007902800270049},
isbn={978-989-758-207-3},
}

TY - CONF

JO - European Space project on Smart Systems, Big Data, Future Internet - Towards Serving the Grand Societal Challenges - EPS Rome 2016
TI - CoherentPaaS - A Coherent and Rich PaaS with a Common Programming Model
SN - 978-989-758-207-3
AU - Jimenez, R.
AU - Patino, M.
AU - Brondino, I.
AU - Vianello, V.
AU - Vilaca, R.
AU - Kolev, B.
AU - Valduriez, P.
AU - Pau, R.
AU - Hatzimanikatis, A.
AU - Spitadakis, V.
AU - Bouras, D.
AU - Panagiotakis, Y.
AU - Saloustros, G.
AU - Papagiannis, A.
AU - Gonzalez-Ferez, P.
AU - Bilas, A.
AU - Zhang, Y.
AU - Kranas, P.
AU - Stamokostas, S.
AU - Moulos, V.
AU - Aisopos, F.
AU - Sabary, F.
AU - Cortesao, L.
AU - Regateiro, D.
AU - Pereira, J.
AU - Oliveira, R.
PY - 2016
SP - 27
EP - 49
DO - 10.5220/0007902800270049
PB - SciTePress