A. Abouzeid, K. Badja-pawlikowski, D. Abadi, A. Silberschatz, and A. Rasin, HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for, Analytical Workloads. PVLDB, vol.2, pp.922-933, 2009.

, Apache Drill-Schema-free SQL Query Engine for Hadoop

A. Impala,

M. Armbrust, R. Xin, C. Lian, Y. Huai, D. Liu et al., Spark SQL: Relational Data Processing in Spark. ACM SIGMOD, pp.1383-1394, 2015.

F. Bugiotti, D. Bursztyn, A. Deutsch, I. Ileana, and I. Manolescu, Invisible Glue: Scalable Self-Tuning Multi-Stores, Conference on Innovative Data Systems Research (CIDR), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01087624

F. Darema, The SPMD model: Past, present and future, Recent Advances in Parallel Virtual Machine and Message Passing Interface, vol.2131, 2001.

S. Dasgupta, K. Coakley, and A. Gupta, Analytics-driven data ingestion and derivation in the AWESOME polystore, IEEE International Conference on Big Data, pp.2555-2564, 2016.
DOI : 10.1109/bigdata.2016.7840897

D. Dewitt, A. Halverson, R. Nehme, S. Shankar, J. Aguilar-saborit et al., Split query processing in Polybase, ACM SIGMOD, pp.1255-1266, 2013.

J. Duggan, A. J. Elmore, M. Stonebraker, M. Balazinska, B. Howe et al., The BigDAWG polystore system, SIGMOD Record, vol.44, issue.2, pp.11-16, 2015.

V. Gadepally, P. Chen, J. Duggan, A. J. Elmore, B. Haynes et al., The BigDawg polystore system and architecture, IEEE High Performance Extreme Computing Conference (HPEC), pp.1-6, 2016.
DOI : 10.1109/hpec.2016.7761636

URL : http://arxiv.org/pdf/1609.07548

H. Hacigümüs, J. Sankaranarayanan, J. Tatemura, J. Lefevre, and N. Polyzotis, Odyssey: A Multi-Store System for, Evolutionary Analytics. PVLDB, vol.6, pp.1180-1181, 2013.

Y. Khan, A. Zimmermann, A. Jha, D. Rebholz-schuhmann, and R. Sahay, Querying web polystores, IEEE International Conference on Big Data, 2017.
DOI : 10.1109/bigdata.2017.8258299

URL : https://hal.archives-ouvertes.fr/emse-01879779

B. Kolev, C. Bondiombouy, P. Valduriez, R. Jimenez-peris, R. Pau et al., The CloudMdsQL Multistore System, pp.2113-2116, 2016.
DOI : 10.1145/2882903.2899400

URL : https://hal.archives-ouvertes.fr/lirmm-01288025

B. Kolev, R. Pau, O. Levchenko, P. Valduriez, R. Jimenez-peris et al., Benchmarking Polystores: the CloudMdsQL Experience, IEEE International Conference on Big Data, pp.2574-2579, 2016.
DOI : 10.1109/bigdata.2016.7840899

URL : https://hal.archives-ouvertes.fr/lirmm-01415582

B. Kolev, P. Valduriez, C. Bondiombouy, R. Jiménez-peris, R. Pau et al., CloudMdsQL: querying heterogeneous cloud data stores with a common language, Distributed and Parallel Databases, vol.34, pp.463-503, 2015.
DOI : 10.1007/s10619-015-7185-y

URL : https://hal.archives-ouvertes.fr/lirmm-01184016

J. Lefevre, J. Sankaranarayanan, H. Hac?gümüs, J. Tatemura, N. Polyzotis et al., MISO: souping up big data query processing with a multistore system, ACM SIGMOD, pp.1591-1602, 2014.

Z. Minpeng and R. Tore, Querying Combined Cloud-based and Relational Databases, Int. Conf. on Cloud and Service Computing, pp.330-335, 2011.

K. W. Ong, Y. Papakonstantinou, and R. Vernoux, The SQL++ Semistructured Data Model and Query Language: A Capabilities Survey of SQL-on-Hadoop, 2014.

T. Özsu and P. Valduriez, Principles of Distributed Database Systems, vol.3, 2011.

, Presto-Distributed Query Engine for Big Data

A. Simitsis, K. Wilkinson, M. Castellanos, and U. Dayal, Optimizing Analytic Data Flows for Multiple Execution Engines, pp.829-840, 2012.

M. Stonebraker and U. Cetintemel, One size fits all: An idea whose time has come and gone (abstract), vol.ICDE, pp.2-11, 2005.

A. Tomasic, L. Raschid, and P. Valduriez, Scaling Access to Heterogeneous Data Sources with DISCO, IEEE Trans. On Knowledge and Data Engineering, vol.10, pp.808-823, 1998.

T. ,

J. Wang, T. Baker, M. Balazinska, D. Halperin, B. Haynes et al., The Myria big data management and analytics system and cloud service, Conference on Innovative Data Systems Research (CIDR, p.2017

T. Yuanyuan, T. Zou, F. Özcan, R. Gonscalves, and H. Pirahesh, Joins for Hybrid Warehouses: Exploiting Massive Parallelism in Hadoop and Enterprise Data Warehouses. EDBT/ICDT Conf, pp.373-384, 2015.