This document discusses in-memory databases (IMDBs) and techniques for recovery and concurrency control in IMDBs. It covers write-ahead logging (WAL), undo/redo techniques, checkpointing approaches, and recovery algorithms used in systems like Dali, Hekaton, TimesTen and others to provide durability, consistency and recoverability for IMDBs.

1. khazeni@ce.sharif.edu
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[1] C. Diaconu, C. Freedman, E. Ismert, P.A. Larson, P.
Mittal, R. Stonecipher, N. Verma and M. Zwilling,
Hekaton: SQL S -Optimized OLTP
Engine, Hekaton: SQL server's memory-optimized
OLTP engine, In Proceedings of the 2013 ACM
SIGMOD International Conference on Management
of Data, 2013.
[2] P.K. Larson, S. Blanas, C. Diaconu, C. Freedman,
J. M. Patel and M. Zwilling, High-Performance
Concurrency Control Mechanisms for Main-Memory
Databases, PVLDB 5(4): 298-309, 2011.
[3] W. Zheng, S. Tu, E. Kohler, and B. Liskov. Fast
databases with fast durability and recovery through
multicore parallelism. In SOSP, 2014.
[4] T. Lahiri, M. A. Neimat, and S. Folkman. Oracle
TimesTen: An In-Memory Database for Enterprise
Applications. IEEE Data Engineering Bulletin, 36(2):
6-13, 2013.
[5] P .A. Bernstein, V. Hadzilacos, and N.Goodman.
Concurrency Control and Recovery in Database
Systems. Addison-Wesley Publishing Company, 1987.
[6] P. Bohannon, R. Rastogi, A. Silberschatz, and
S. Sudarshan. Multi-level recovery in the Dali storage
manager. Technical report, AT&T Bell Labs Internal
Report, 1995.
[7] M. H. Eich. Main memory database recovery. In
Proceedings of ACM-IEEE Fall Joint Computer
Conference, pages 1226-1232, 1986. 5
[8] M. H. Eich. A classification and comparison of main
memory database recovery techniques. In Proceedings
of the IEEE International Conference on Data
Engineering, pages 332-339, 1987.
[9] H. Garcia-Molina and C. A. Polyzois. Issues in
disaster recovery, In 35th IEEE Compcon 90, pages
573-577, 1990.
[10] H. Garcia-Molina and K. Salem, Main memory
database systems: An overview. IEEE Transactions on
Knowledge and Database Engineering, 4(6):509-516,
1992.
[11] J. Gray, Notes on data base operating systems. In
R. Bayer, R.N. Graham, and G. Seegmueller, editors,
Lecture Notes on Computer Science Volume 60.
Springer-Verlag, 1978.
[12] J. Gray and A. Reuter. Transaction Processing:
Concepts and Techniques. Morgan Kaufmann
Publishers, 1993.
[13] L. Gruenwald and M. H. Eich. MMDB reload
algorithms. In Proceedings of the ACM SIGMOD
International Conference on Management of Data,
pages 397-405, 1991.
[14] T. Haeder and A. Reuter, Principles of transaction-
oriented database recovery, ACM Computing Surveys,
15(4):287-317, 1983.
[15] Robert B. Hagmann. A crash recovery scheme for a
memory resident database system. IEEE Transactions
on Computers, C-35(9):839-843, 1986.
[16] H. V. Jagadish, D. Lieuwen, R. Rastogi, A.
Silberschatz, and S. Sudarshan. Dali: A high
performance main memory storage manager. In
Proceedings of the 20th Conference on Very Large
Datab ases, Morgan Kaufman pubs. (Los Altos CA),
1994.
[17] H. V. Jagadish, A. Silberschatz, and S. Sudarshan.
Recovering from main-memory lapses. In
Proceedings of the 19th Conference on Very Large
Databases, Mor gan Kaufman pubs. (Los Altos CA),
D, 1993.
[18] T. J. Lehman and M. J. Carey . A recovery algorithm
for a high-performance memory-resident database
system. In 19 ACM SIGMOD Conf. on the
Management of Data, 1987.
[19] T. J. Lehman and M. J. Carey . A recovery algorithm
for a high-performance memory-resident database
system. In Proceedings of the 1987 ACM-SIGMOD
International Conference on Management of Data,
pages 104-117, 1987.
[20] E. Levy and A. Silberschatz. Incremental recovery in
main memory database systems. IEEE Transactions
on Knowledge and Data Engineering, 4(6), 1992.
[21] K. Li and J. F. Naughton. Multiprocessor main
memory transaction processing. In Proceedings of
International Symposium on Databases in Parallel
and Distributed Systems,1988.
[22] X. Li, M. H. Eich, V.J. Joseph, Z. Gulzar, C.H. Corti,
and M. Nascimento. Checkpointing and recovery in
partitioned main memory databases. In Proc.
IASTED/ISMM International Conference on
Intelligent Information Management Systems, 1995.
[23] J. L. Lin and M. H. Dunham. Dynamic segmented
fuzzy checkpointing for main memory databases.
1995.
[24] J.L. Lin and M. H. Eich, Segmented fuzzy
checkpointing for main memory databases. Technical
Report CSE9442, Southern Methodist University,
Dept. of Computer Science and Engineering, Dallas
(TX), 1994.
[25] Jim Lyon. Tandem's remote data facility, In 35th IEEE
Compcon 90, pages 562-567, 1990.
[26] K. Rothermel and C. Mohan, Aries/nt: A recovery
method based on write-ahead logging for nested
transactions. In Proceedings of the Fifteenth

11. International Conference on Very Large DataBases,
pages 337-346, 1989
[27] K. Salem and H. Garcia-Molina. Checkpointing
memory-resident databases. In Proc. IEEE CS Intl.
Conf. No. 5 on Data Engineering, 1989.
[28] Joost S. M. Verhofstad. Recovery techniques for
database systems, ACM Computing Surveys,
0(2):167-195, 1978.
1- Dynamic Random Access Memory (DRAM)
2- In-memory Database (IMDB)
3- Disk Resident Database (DRDB)
4- Throughout
5- Automatic Teller Machine (ATM)
6- Reserve
7- Telephone switching
8- Random Access Memory (RAM)
9- Nonvolatile memory
10- Archive memory
11- Checkpoint
12- Reloading
13- After image
14- Before image
15- Begin Transaction (BT)
16- End Transaction (ET)
17- Begin Checkpoint (BC)
18- End Checkpoint (EC)
19- Offset
20- Idempotence
21- Fuzzy
22- Write Ahead Logging (WAL)
23- Undone
24- Solid-State Disk (SSD)
25- Input/Output (I/O)
26- Non-fuzzy
27- Log-driven
28- Hagmann
29- Dumping
30- Salem
31- Garcia-Molina
32- Dirty data
33- Lin
34- Dunham
35- Segmented
36- Moving window
37- Round-robin
38- Li
39- Backward
40- Long-lived
41- Transaction-consistent
42- Action-consistent
43- Lehman
44- Carey
45- Index
46- Jagadish
47- Occurrence frequency of the reload process
48- Pareto
49- Multicore parallelism
50- Reload prioritization
51- Access frequency
52- Transaction deadline
53- Gruenwald
54- Ordered Reload with Prioritization (ORP)
55- Smart Reload (SR)
56- Frequency Reload (FR)
57- Reload granularity
58- Preempt
59- Atomic
60- Levy
61- Silberschatz
62- Multi-level
63- Group commit
64- Optimistic multi-version
65- Latch
66- Bottleneck
67- Checkpoint file inventory
68- Indexing
69- Timestamp range
70- Buffer
71- Root page
72- Thread
73- Hewlett-Packard (HP)
74- Multi-threaded logging mechanism
75- Delayed-durability