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OpenSource RDBMS

RDBMS Language Column or Row Cloud Native Github Repo Affliated Organization
Clickhouse C++ Column No https://github.com/ClickHouse/ClickHouse https://www.clickhouse.com
Greenplum DB C/C++ Row No https://github.com/greenplum-db/gpdb https://docs.vmware.com/en/VMware-Greenplum/index.html
C-Store C++ Column No https://github.com/eyalroz/c-store https://www.vertica.com/
MonetDB C Column No https://github.com/MonetDB/MonetDB https://www.monetdbsolutions.com/
MySQL C++/C Row No https://github.com/mysql/mysql-server https://dev.mysql.com/
MariaDB C++/C Row No https://github.com/MariaDB/server https://mariadb.com/
PostgreSQL C Row No https://github.com/postgres/postgres https://www.postgresql.org/, https://www.enterprisedb.com/
YugabyteDB C/C++ Column Yes https://github.com/yugabyte/yugabyte-db https://www.yugabyte.com/
FirebirdSQL C++/C Row No https://github.com/FirebirdSQL/firebird https://firebirdsql.org/
CockroachDB Go Column Yes https://github.com/cockroachdb/cockroach https://www.cockroachlabs.com/product/
TiDB Go Column Yes https://github.com/pingcap/tidb https://www.pingcap.com/

OpenSource NoSQL DBMS

DBMS Language Cloud Native Github Repo Affliated Organization
ScyllaDB C++ Yes https://github.com/scylladb/scylladb https://www.scylladb.com
MongoDB C++ Yes https://github.com/mongodb/mongo https://www.mongodb.com
Cassandra Java Yes https://github.com/apache/cassandra https://www.datastax.com/
Redis C Yes https://github.com/redis/redis https://redis.io/
OrientDB Java Yes https://github.com/orientechnologies/orientdb https://orientdb.org/

Important Research Papers and Github Repos

General Query Optimization Related

Mohamed A.S, Lyublena A, Venkatesh R, Amr E-H, Zhongxian G, etc. (2014) Orca: a modular query optimizer architecture for big data SIGMOD '14: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, June 2014, pp. 337-348, PDF

Mario A.M, Yuan S, Michael K and Saman K.H (2015) ALgorithm selection for black-box continuous optimization problems: a survey on methods and challenges Information Sciences, Vol. 317(1), pp. 224-245, PDF

Viktor L, Andrey G, Atanas M, Peter B, Alfons K and Thomas N (2015) How good are query optimizers, really? Proceedings of the VLDB Endowment, Vol. 9(3), pp. 204-215, PDF

Learned Query Optimizer (LQO)

Neo

Ryan M, Parimarjan N, Hongzi M, Chi Z, Mohammad A, Tim K, Olga P and Nesime T (2019) Neo: a learned query optimizer Proceedings of the VLDB Endowment, Vol 12(11), pp. 1705-1718 PDF

Bao

Ryan M, Parimarjan N, Hongzi M, Nesime T, Mohammad A and Time K (2021) Bao: making learned query optimization practical SIGMOD '21: Proceedings of the 2021 International Conference on Management of Data, June 2021, pp. 1275-1288, PDF, Slides

Balsa

Zongheng Y, Wei-Lin C, Sifei L, Gautam M, Michael L and Ion S (2022) Balsa: learning a query optimizer without expert demonstrations SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data, June 2022, pp. 931-944 PDF

Lero

Rong Z, Wei C, Bolin D, Xingguang C, Andreas P, Ziniu W and Jingren Z (2023) Lero: a learning-to-rank query optimizer Proceedings of the VLDB Endowment, Vol. 16(6), pp. 1466-1479 PDF

LEON

Xu C, Haitian C, Zibo L, Shuncheng L, Jinghong W, Kai Z, Han S and Kai Z (2023) LEON: a new framework for ML-aided query optimization Proceedings of the VLDB Endowment, Vol. 16(9), pp. 2261-2273 PDF

LOGER

Tianyi C, Jun G, Hedui C and Yaofeng T (2023) Loger: a learned optimizer towards generating efficient and robust query execution plans Proceedings of the VLDB Endowment, Vol. 16(7), pp. 1777-1789 PDF

HybridQO

Xiang Y, Chengliang C, Guoliang L and Jiabin L (2022) Cost-based or learning-based?: a hybrid query optimizer for query plan selection Proceedings of the VLDB Endowment, Vol. 15(13), pp. 3924-3936 PDF

AutoSteer

Christoph A, Nesime T, David C, Zhenggang X and Prithviraj P (2023) AutoSteer: learned query optimization for any SQL database Proceedings of the VLDB Endowment, Vol. 16(12), pp. 3515-3527, PDF

PilotScope

Rong Z, Lianggui W, Wenqing W, Di W, Jiazheng P, Yifan W, etc. (2024) PilotScope: steering databases with machine learning drivers Proceedings of the VLDB Endowment, Vol 17(5), pp. 980-993 PDF

Review

Claude L, Pavel S and Kurt S (2023) Is your learned query optimizer behaving as you expected? a machine learning perspective PVLDB, Vol. 17, 2023-2024, PDF

Guy Lohman (2014) Is query optimization a "solved" problem? ACM Sigmod Blog PDF

Bandit Algorithm Related

Olivier C and Lihong L (2011) An empirical evaluation of thompson sampling NIPS'11: Proceedings of the 24th International Conference on Neural Information Processing Systems, Dec. 2011, pp. 2249-2257 PDF

Database Related Paper Lists on Github

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