A collection of demonstrations showcasing how stream processing can be used to solve real-world problems.
-
Updated
Aug 21, 2024 - Python
A collection of demonstrations showcasing how stream processing can be used to solve real-world problems.
Kafka Streams for Low Code Environments
A scalable, declarative, low-code framework for real-time and batch feature calculation/management (quant finance, anomaly/fraud detection, etc.), predictive ML training/inference and simulation. Built on top of Ray
Postgres Logical Replication plugin for benthos
A data ingestion adaptor to plug data from source to sink with a configuration based pipeline
Repository containing configurations for the benchmarks included in RSP Lab Suite
This is the graduate thesis work for my Computer Science Major
Simple stream processing library for synchronous or parallel and non-distributed execution.
The aim of this big data project is to design and implement a big data system that can provide real-time context-aware recommendations to drivers on the level of possible danger.
simple stream processing with event driven services. using nodejs, rabbitmq, apache kafka, mongodb and redis
The repo simulates query load, optimizes performance, and offers practical guidance for building data warehouses with Azure Synapse Analytics. 🚀
Stream & aggregate tweets containing a set of track terms in memory and write aggregates to rocks db. Aggregates include top hashtags, top mentions and top retweets. Contains a local executable that can run forever, computing aggregates and storing results in a local rocks DB. Also has repl mode for querying results from the db.
A sample real-time streaming analytics application with Spark Structured Streaming and Kafka.
GitHub Analytics Using Apache Pulsar - Streaming Analytics Solution
Add a description, image, and links to the streamprocessing topic page so that developers can more easily learn about it.
To associate your repository with the streamprocessing topic, visit your repo's landing page and select "manage topics."