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Apache IoTDB
- Source :
- Proceedings of the VLDB Endowment. 13:2901-2904
- Publication Year :
- 2020
- Publisher :
- Association for Computing Machinery (ACM), 2020.
-
Abstract
- The amount of time-series data that is generated has exploded due to the growing popularity of Internet of Things (IoT) devices and applications. These applications require efficient management of the time-series data on both the edge and cloud side that support high throughput ingestion, low latency query and advanced time series analysis. In this demonstration, we present Apache IoTDB managing time-series data to enable new classes of IoT applications. IoTDB has both edge and cloud versions, provides an optimized columnar file format for efficient time-series data storage, and time-series database with high ingestion rate, low latency queries and data analysis support. It is specially optimized for time-series oriented operations like aggregations query, down-sampling and sub-sequence similarity search. An edge-to-cloud time-series data management application is chosen to demonstrate how IoTDB handles time-series data in real-time and supports advanced analytics by integrating with Hadoop and Spark. An end-to-end IoT data management solution is shown by integrating IoTDB with PLC4x, Calcite, and Grafana.
- Subjects :
- Database
business.industry
Computer science
Data management
General Engineering
020206 networking & telecommunications
Cloud computing
02 engineering and technology
computer.software_genre
File format
Analytics
Spark (mathematics)
Computer data storage
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Latency (engineering)
business
computer
Time series database
Subjects
Details
- ISSN :
- 21508097
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- Proceedings of the VLDB Endowment
- Accession number :
- edsair.doi...........26cb9e2f42891fc5f30383302fbeebf1
- Full Text :
- https://doi.org/10.14778/3415478.3415504