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Comparison – Disk vs. MOT

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Comparison – Disk vs. MOT

The following table briefly compares the various features of the openGauss disk-based storage engine and the MOT storage engine.

Table 1 Comparison – Disk-based vs. MOT

FeatureopenGaussopenGauss
Intel x86 + Kunpeng ARMYesYes
SQL and Feature-set Coverage100%98%
Scale-up (Many-cores, NUMA)Low EfficiencyHigh Efficiency
ThroughputHighExtremely High
LatencyLowExtremely Low
Distributed (Cluster Mode)YesYes
Isolation LevelsREAD COMMITTEDREPEATABLE READREAD COMMITTEDREPEATABLE READ
Concurrency ControlPessimistic + MVCCOptimistic + MVCC
Data Capacity (Data + Index)UnlimitedLimited to DRAM
Native CompilationNoYes
Replication, RecoveryYesYes
Replication Options2 (sync, async)3 (sync, async, group-commit)

Appendices

References

[1] Y. Mao, E. Kohler, and R. T. Morris. Cache craftiness for fast multicore key-value storage. In Proc. 7th ACM European Conference on Computer Systems (EuroSys), Apr. 2012.

[2] K. Ren, T. Diamond, D. J. Abadi, and A. Thomson. Low-overhead asynchronous checkpointing in main-memory database systems. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data, 2016.

[3] https://e.huawei.com/en/products/servers/taishan-server/taishan-2280-v2.

[4] https://e.huawei.com/en/products/servers/taishan-server/taishan-2480-v2.

[5] Tu, S., Zheng, W., Kohler, E., Liskov, B., and Madden, S. Speedy transactions in multicore in-memory databases. In Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles (New York, NY, USA, 2013), SOSP ’13, ACM, pp. 18–32.

[6] H. Avni at al. Industrial-Strength OLTP Using Main Memory and Many-cores, VLDB 2020.

[7] Bernstein, P. A., and Goodman, N. Concurrency control in distributed database systems. ACM Comput. Surv. 13, 2 (1981), 185–221.

[8] Felber, P., Fetzer, C., and Riegel, T. Dynamic performance tuning of word-based software transactional memory. In Proceedings of the 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP 2008, Salt Lake City, UT, USA, February 20-23, 2008 (2008),

pp. 237–246.

[9] Appuswamy, R., Anadiotis, A., Porobic, D., Iman, M., and Ailamaki, A. Analyzing the impact of system architecture on the scalability of OLTP engines for high-contention workloads. PVLDB 11, 2 (2017),

121–134.

[10] R. Sherkat, C. Florendo, M. Andrei, R. Blanco, A. Dragusanu, A. Pathak, P. Khadilkar, N. Kulkarni, C. Lemke, S. Seifert, S. Iyer, S. Gottapu, R. Schulze, C. Gottipati, N. Basak, Y. Wang, V. Kandiyanallur, S. Pendap, D. Gala, R. Almeida, and P. Ghosh. Native store extension for SAP HANA. PVLDB, 12(12):

2047–2058, 2019.

[11] X. Yu, A. Pavlo, D. Sanchez, and S. Devadas. Tictoc: Time traveling optimistic concurrency control. In Proceedings of the 2016 International Conference on Management of Data, SIGMOD Conference 2016, San Francisco, CA, USA, June 26 - July 01, 2016, pages 1629–1642, 2016.

[12] V. Leis, A. Kemper, and T. Neumann. The adaptive radix tree: Artful indexing for main-memory databases. In C. S. Jensen, C. M. Jermaine, and X. Zhou, editors, 29th IEEE International Conference on Data Engineering, ICDE 2013, Brisbane, Australia, April 8-12, 2013, pages 38–49. IEEE Computer Society, 2013.

[13] S. K. Cha, S. Hwang, K. Kim, and K. Kwon. Cache-conscious concurrency control of main-memory indexes on shared-memory multiprocessor systems. In P. M. G. Apers, P. Atzeni, S. Ceri, S. Paraboschi, K. Ramamohanarao, and R. T. Snodgrass, editors, VLDB 2001, Proceedings of 27th International Conference on Very Large Data Bases, September 11-14, 2001, Roma, Italy, pages 181–190. Morga Kaufmann, 2001.

Glossary

Table 2 Glossary

AcronymDefinition/Description
2PL2-Phase Locking
ACIDAtomicity, Consistency, Isolation, Durability
APAnalytical Processing
ARMAdvanced RISC Machine, a hardware architecture alternative to x86
CCConcurrency Control
CPUCentral Processing Unit
DBDatabase
DBADatabase Administrator
DBMSDatabase Management System
DDLData Definition Language. Database Schema management language
DMLData Modification Language
ETLExtract, Transform, Load or Encounter Time Locking
FDWForeign Data Wrapper
GCGarbage Collector
HAHigh Availability
HTAPHybrid Transactional-Analytical Processing
IoTInternet of Things
IMIn-Memory
IMDBIn-Memory Database
IRIntermediate Representation of a source code, used in compilation and optimization
JITJust In Time
JSONJavaScript Object Notation
KVKey Value
LLVMLow-Level Virtual Machine, refers to a compilation code or queries to IR
M2MMachine-to-Machine
MLMachine Learning
MMMain Memory
MOMemory Optimized
MOTMemory Optimized Tables storage engine (SE), pronounced as /em/ /oh/ /tee/
MVCCMulti-Version Concurrency Control
NUMANon-Uniform Memory Access
OCCOptimistic Concurrency Control
OLTPOnline Transaction Processing
PGPostgreSQL
RAWReads-After-Writes
RCReturn Code
RTORecovery Time Objective
SEStorage Engine
SQLStructured Query Language
TCOTotal Cost of Ownership
TPTransactional Processing
TPC-CAn On-Line Transaction Processing Benchmark
Tpm-CTransactions-per-minute-C. A performance metric for TPC-C benchmark that counts new-order transactions.
TVMTiny Virtual Machine
TSOTime Sharing Option
UDTUser-Defined Type
WALWrite Ahead Log
XLOGA PostgreSQL implementation of transaction logging (WAL - described above)

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