Skip to main content

Transactional Stream Processing

  • Living reference work entry
  • First Online:
Book cover Encyclopedia of Database Systems
  • 97 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Recommended Reading

  1. Hwang JH, Balazinska M, Rasin A, Cetintemel U, Stonebraker M, Zdonik S. High-availability algorithms for distributed stream processing. In: ICDE; 2005. p. 779–90.

    Google Scholar 

  2. Toshniwal A, Taneja S, Shukla A, Ramasamy K, Patel JM, Kulkarni S, et al. Storm @Twitter. In: SIGMOD; 2014. p. 147–56.

    Google Scholar 

  3. Zaharia M, Das T, Li H, Hunter T, Shenker S, Stoica I. Discretized streams: fault-tolerant streaming computation at scale. In: SOSP; 2013. p. 423–38.

    Google Scholar 

  4. Chandramouli B, Goldstein J, Barnett M, DeLine R, Fisher D, Platt JC, et al. Trill: a high-performance incremental query processor for diverse analytics. PVLDB. 2014;8(4):401–12.

    Google Scholar 

  5. Akidau T, Bradshaw R, Chambers C, Chernyak S, Fernandez-Moctezuma RJ, Lax R, et al. The dataflow model: a practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing. PVLDB. 2015;8(12): 1792–1803.

    Google Scholar 

  6. Meehan J, Tatbul N, Zdonik S, Aslantas C, Cetintemel U, Du J, et al. S-store: streaming meets transaction processing. PVLDB. 2015;8(13): 2134–45.

    Google Scholar 

  7. Ramnarayan J, Mozafari B, Wale S, Menon S, Kumar N, Bhanawat H, et al. SnappyData: streaming, transactions, and interactive analytics in a unified engine. In: SIGMOD; (2016, to appear).

    Google Scholar 

  8. Arasu A, Babu S, Widom J. The CQL continuous query language: semantic foundations and query execution. VLDB J. 2006;15(2):121–42.

    Article  Google Scholar 

  9. Golab L, Bijay KG, Ozsu MT. On concurrency control in sliding window queries over data streams. In: EDBT; 2006. p. 608–26.

    Google Scholar 

  10. Wang D, Rundensteiner EA, Ellison RT. Active complex event processing over event streams. PVLDB. 2011;4(10):634–45.

    Google Scholar 

  11. Balazinska M, Balakrishnan H, Madden SR, Stonebraker M. Fault-tolerance in the Borealis distributed stream processing system. ACM TODS. 2008;33(1):3:1–3:44.

    Google Scholar 

  12. Akidau T, Balikov A, Bekiroglu K, Chernyak S, Haberman J, Lax R, et al. MillWheel: fault-tolerant stream processing at Internet scale. PVLDB. 2013;6(11):734–46.

    Google Scholar 

  13. Botan I, Fischer PM, Kossmann D, Tatbul N. Transactional stream processing. In: EDBT; 2012. p. 204–15.

    Google Scholar 

  14. Kreps J, Narkhede N, Rao J. Kafka: a distributed messaging system for log processing. In: NetDB workshop; 2011.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nesime Tatbul .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media LLC

About this entry

Cite this entry

Tatbul, N. (2016). Transactional Stream Processing. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_80704-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_80704-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

Publish with us

Policies and ethics