H-store

Author:

Kallman Robert1,Kimura Hideaki1,Natkins Jonathan1,Pavlo Andrew1,Rasin Alexander1,Zdonik Stanley1,Jones Evan P. C.2,Madden Samuel2,Stonebraker Michael2,Zhang Yang2,Hugg John3,Abadi Daniel J.4

Affiliation:

1. Brown University

2. Massachusetts Institute of Technology

3. Vertica Inc.

4. Yale University

Abstract

Our previous work has shown that architectural and application shifts have resulted in modern OLTP databases increasingly falling short of optimal performance [10]. In particular, the availability of multiple-cores, the abundance of main memory, the lack of user stalls, and the dominant use of stored procedures are factors that portend a clean-slate redesign of RDBMSs. This previous work showed that such a redesign has the potential to outperform legacy OLTP databases by a significant factor. These results, however, were obtained using a bare-bones prototype that was developed just to demonstrate the potential of such a system. We have since set out to design a more complete execution platform, and to implement some of the ideas presented in the original paper. Our demonstration presented here provides insight on the development of a distributed main memory OLTP database and allows for the further study of the challenges inherent in this operating environment.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

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1. What Goes Around Comes Around... And Around...;ACM SIGMOD Record;2024-07-30

2. OLAP on Modern Chiplet-Based Processors;Proceedings of the VLDB Endowment;2024-07

3. Distributed Transaction Processing in Untrusted Environments;Companion of the 2024 International Conference on Management of Data;2024-06-09

4. Amazon MemoryDB: A Fast and Durable Memory-First Cloud Database;Companion of the 2024 International Conference on Management of Data;2024-06-09

5. PolarDB-MP: A Multi-Primary Cloud-Native Database via Disaggregated Shared Memory;Companion of the 2024 International Conference on Management of Data;2024-06-09

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