https://github.com/rbeeli/streamops.jl
Composable operations for efficient online processing of realtime data streams using directed graphs.
https://github.com/rbeeli/streamops.jl
graph julia online processing realtime streaming
Last synced: about 2 months ago
JSON representation
Composable operations for efficient online processing of realtime data streams using directed graphs.
- Host: GitHub
- URL: https://github.com/rbeeli/streamops.jl
- Owner: rbeeli
- License: apache-2.0
- Created: 2023-11-19T00:34:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2026-04-12T10:21:50.000Z (2 months ago)
- Last Synced: 2026-04-12T12:16:11.113Z (2 months ago)
- Topics: graph, julia, online, processing, realtime, streaming
- Language: Jupyter Notebook
- Homepage:
- Size: 1.18 MB
- Stars: 4
- Watchers: 1
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Agents: AGENTS.md
Awesome Lists containing this project
README
# StreamOps.jl
Composable operations for efficient online processing of realtime and historical data streams using directed graphs.
## Background
Real-time data processing is a common requirement in many applications such as IoT, monitoring, telemetry systems, streaming analytics, financial trading, etc.
In these applications, data is continuously generated and needs to be processed in real-time in order to extract insights and take decisions.
Algorithms processing continuous data streams are able to process data as it arrives using efficient [online algorithms](https://en.wikipedia.org/wiki/Online_algorithm).
Online algorithms update their state with each new data point and do not require the entire dataset to be loaded into memory.
An update usually consists of a single data point. In the best case, the update is processed in constant time and takes constant memory.