Name
Abstract | ||
|---|---|---|
Many organizations require the ability to manage high-volume high-speed streaming data to perform analysis and other tasks in real-time. In this work, we present the Information Streaming Engine, a high-performance data stream processing system capable of scaling to high data volumes while maintaining very low-latency. The Information Streaming Engine adopts a declarative approach which enables processing and manipulation of data streams in a simple manner. Our evaluation demonstrates the high levels of performance achieved when compared to existing systems. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.5220/0005938000130024 | DATA |
Keywords | Field | DocType |
Data Stream Processing, High-performance Computing, Low-latency, Distributed Systems | Data stream processing,Data stream mining,Supercomputer,Computer science,Real-time computing,Streaming data,Latency (engineering),Scaling,Database | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Cappellari | 1 | 2 | 2.05 |
| Soon Ae Chun | 2 | 893 | 100.67 |
| Mark Roantree | 3 | 240 | 40.76 |