The list referenced papers are listed from. 《Hybrid Transactional/Analytical Processing: A Survey.》, from IBM Research.

[1] Apache Parquet. https://parquet.apache.org/.
[2] R. Appuswarmy, M. Karpathiotakis, D. Porobic, and A. Ailamaki. The Case For Heterogeneous HTAP. In
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[3] M. Armbrust, R. S. Xin, C. Lian, Y. Huai, D. Liu,J. K. Bradley, X. Meng, T. Kaftan, M. J. Franklin,
A. Ghodsi, and M. Zaharia. Spark SQL: Relational Data Processing in Spark. In SIGMOD, pages 1383–1394, 2015.
[4] J. Arulraj, A. Pavlo, and P. Menon. Bridging the Archipelago Between Row-Stores and Column-Stores for Hybrid Workloads. In SIGMOD, pages 583–598, 2016.
[5] R. Barber, C. Garcia-Arellano, R. Grosman, R. Mueller, V. Raman, R. Sidle, M. Spilchen, A. Storm, Y. Tian, P. T¨ozun, D. Zilio, M. Huras, ¨
G. Lohman, C. Mohan, F. Ozcan, and H. Pirahesh. ¨Evolving Databases for New-Gen Big Data Applications. In CIDR, 2017.
[6] A. Boehm, J. Dittrich, N. Mukherjee, I. Pandis, and R. Sen. Operational analytics data management systems. PVLDB, 9:1601–1604, 2016.
[7] P. Boncz, M. Zukowski, and N. Nes. MonetDB/X100: Hyper-Pipelining Query Execution. In CIDR, 2005.
[8] Apache Cassandra. http://cassandra.apache.org.
[9] A. Costea, A. Ionescu, B. R˘aducanu, M. Switakowski, C. Bˆarca, J. Sompolski, A. Luszczak, M. Szafra´nski, G. de Nijs, and P. Boncz. Vectorh: Taking
sql-on-hadoop to the next level. In SIGMOD ’16, pages 1105–1117, 2016.
[10] Danial Abadi and Shivnath Babu and Fatma Ozcan ¨ and Ippokratis Pandis. Tutorial: SQL-on-Hadoop Systems. PVLDB, 8, 2015.
[11] IBM dashDB. http://www.ibm.com/analytics/us/en/technology/cloud-data-services/dashdb.
[12] DataStax Spark Cassandra Connector. https://github.com/datastax/spark-cassandra-connector.
[13] C. Diaconu, C. Freedman, E. Ismert, P.-˚A. Larson, P. Mittal, R. Stonecipher, N. Verma, and M. Zwilling. Hekaton: SQL Server’s memory-optimized OLTP
engine. In SIGMOD, pages 1243–1254, 2013.
[14] F. F¨arber, N. May, W. Lehner, P. Große, I. Muller, ¨ H. Rauhe, and J. Dees. The SAP HANA Database –An Architecture Overview. IEEE DEBull,35(1):28–33, 2012.
[15] S. Gray, F. Ozcan, H. Pereyra, B. van der Linden, and ¨A. Zubiri. IBM Big SQL 3.0: SQL-on-Hadoop without compromise. http://public.dhe.ibm.com/common/ssi/
ecm/en/sww14019usen/SWW14019USEN.PDF, 2014.
[16] SAP HANA Vora. http://go.sap.com/product/data-mgmt/hana-vora-hadoop.html.
[17] Apache HBase. https://hbase.apache.org/.
[18] Hive Transactions. http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.3.0/bk dataintegration/content/hive-013-feature-transactions.html.[19] A. Kemper and T. Neumann. HyPer – A Hybrid OLTP&OLAP Main Memory Database System Based on Virtual Memory Snapshots. In ICDE, pages 195–206, 2011.
[20] M. Kornacker, A. Behm, V. Bittorf, T. Bobrovytsky,C. Ching, A. Choi, J. Erickson, M. Grund, D. Hecht, M. Jacobs, I. Joshi, L. Kuff, D. Kumar, A. Leblang,
N. Li, I. Pandis, H. Robinson, D. Rorke, S. Rus, J. Russell, D. Tsirogiannis, S. Wanderman-Milne, and M. Yoder. Impala: A modern, open-source SQL engine for Hadoop. In CIDR, 2015.
[21] Apache Kudu. https://kudu.apache.org/.
[22] T. Lahiri, M.-A. Neimat, and S. Folkman. Oracle TimesTen: An In-Memory Database for Enterprise Applications. IEEE DEBull, 36(3):6{13, 2013.
[23] A. Lamb, M. Fuller, R. Varadarajan, N. Tran, B. Vandiver, L. Doshi, and C. Bear. The Vertica Analytic Database: C-store 7 Years Later. PVLDB, 5(12):1790{1801, 2012.
[24] MemSQL. http://www.memsql.com/.
[25] C. Mohan. History Repeats Itself: Sensible and NonsenSQL Aspects of the NoSQL Hoopla. In EDBT, 2013.
[26] B. Mozafari, J. Ramnarayan, S. Menon, Y. Mahajan, S. Chakraborty, H. Bhanawat, and K. Bachhav.SnappyData: A Unified Cluster for Streaming, Transactions and Interactice Analytics. In CIDR, 2017.
[27] Apache ORC. https://orc.apache.org/.
[28] A. Pavlo, J. Arulraj, L. Ma, P. Menon, T. C. Mowry, M. Perron, A. Tomasic, D. V. Aken, Z. Wang, and T. Zhang. Self-Driving Database Management
Systems. In CIDR, 2017.
[29] Apache Phoenix. http://phoenix.apache.org.
[30] V. Raman, G. Attaluri, R. Barber, N. Chainani, D. Kalmuk, V. KulandaiSamy, J. Leenstra, S. Lightstone, S. Liu, G. M. Lohman, T. Malkemus,
R. Mueller, I. Pandis, B. Schiefer, D. Sharpe, R. Sidle, A. Storm, and L. Zhang. DB2 with BLU Acceleration: So Much More than Just a Column Store. PVLDB, 6:1080{1091, 2013.
[31] RocksDB. http://rocksdb.org/.
[32] Roshan Sumbaly and others. Serving large-scale batch computed data with project Voldemort. In Proc. of the 10th USENIX conference on File and Storage Technologies, 2012.
[33] Splice Machine. http://www.splicemachine.com/.
[34] M. Stonebraker and U. Cetintemel. “One Size Fits All”: An Idea Whose Time Has Come and Gone. In ICDE, pages 2{11, 2005.
[35] M. Stonebraker and A. Weisberg. The VoltDB Main
Memory DBMS. IEEE Data Eng. Bull., 36(2):21{27, 2013.
[36] A. Thusoo, J. S. Sarma, N. Jain, Z. Shao, P. Chakka, N. Zhang, S. Anthony, H. Liu, and R. Murthy. Hive –
A Petabyte Scale Data Warehouse Using Hadoop. In ICDE, 2010.
[37] S. Tu, W. Zheng, E. Kohler, B. Liskov, and S. Madden. Speedy Transactions in Multicore In-memory Databases. In SOSP, pages 18{32, 2013.
[38] Z. Zhang. Spark-on-HBase: Dataframe Based HBase Connector. http://hortonworks.com/blog/spark-hbase-dataframe-based-hbase-connector.