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- Mahmood, Khalid, et al.
(författare)
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Wrapping a NoSQL Datastore for Stream Analytics
- 2020
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Ingår i: 2020 IEEE 21st International Conference On Information Reuse And Integration For Data Science (IRI 2020). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 301-305
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Konferensbidrag (refereegranskat)abstract
- With the advent of the Industrial Internet of Things (IIoT) and Industrial Analytics, numerous application scenarios emerge, where business and mission-critical decisions depend upon large scale analytics of sensor streams. However, very large volumes of data from data streams generated at a high rate pose substantial challenges in providing scalable analytics from existing Database Management Systems (DBMS). While scalability can be provided by high-performance distributed datastores, due to the simple query operations, access to high-level query-based data analytics is usually limited. This work combines high-level query-based data analytics capabilities with high-performance distributed scalability by applying a wrapper-mediator approach. The Amos II extensible main-memory DBMS provides online query processing data analytics engine in front of the MongoDB distributed NoSQL datastore to support large-scale distributed data analytics over persisted data streams. Thus, the implemented system enables query-based online data stream analytics over persisted data streams stored/logged in distributed NoSQL datastores.
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