A Survey of Data Stream Processing Tools

In current international context boundaries set for applications are being pushed by the emergence of bursty and time-varying data streams required to be processed in near real-time. Furthermore, traditional techniques for data mining cannot be applied to data streams. Thus, stream-based applications must exhibit to excel at a plurality of requirements. According to defined rules presented in previous promulgated researches on this subject we differ stream-based applications and evaluate their aptitude to stream sources management. By this work we intend to present features and drawbacks of existing software coming from both industry and academic world, along with outlining our contribution to this field.

[1]  Marcin Gorawski,et al.  Research on the Stream ETL Process , 2014, BDAS.

[2]  Ying Xing,et al.  The Design of the Borealis Stream Processing Engine , 2005, CIDR.

[3]  Badrish Chandramouli,et al.  The extensibility framework in Microsoft StreamInsight , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[4]  Michael Stonebraker,et al.  The 8 requirements of real-time stream processing , 2005, SGMD.

[5]  Alfons Kemper,et al.  StreamGlobe: Processing and Sharing Data Streams in Grid-Based P2P Infrastructures , 2005, VLDB.

[6]  B. Seeger,et al.  PIPES : A Multi-Threaded Publish-Subscribe Architecture for Continuous Queries over Streaming Data Sources , 2003 .

[7]  Marcin Gorawski,et al.  Query Processing Using Negative and Temporal Tuples in Stream Query Engines , 2009, CEE-SET.

[8]  Qiang Chen,et al.  Aurora : a new model and architecture for data stream management ) , 2006 .

[9]  Marcin Gorawski,et al.  StreamAPAS: Query Language and Data Model , 2009, 2009 International Conference on Complex, Intelligent and Software Intensive Systems.

[10]  Walid G. Aref,et al.  Incremental Evaluation of Sliding-Window Queries over Data Streams , 2007 .

[11]  Jennifer Widom,et al.  STREAM: The Stanford Stream Data Manager , 2003, IEEE Data Eng. Bull..

[12]  Marcin Gorawski,et al.  Evaluation and Development Perspectives of Stream Data Processing Systems , 2013, CN.

[13]  Jonathan Goldstein,et al.  Consistent Streaming Through Time: A Vision for Event Stream Processing , 2006, CIDR.