streaming-analytics

🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.

SDK for Visual Memory Search with Smart Glasses

Serverless multi-protocol + multi-destination event collection system.

Adapter for dbt that executes dbt pipelines on Apache Flink

📡 Real-time data pipeline with Kafka, Flink, Iceberg, Trino, MinIO, and Superset. Ideal for learning data systems.

Composable Streaming Intelligence

Different flavours of CUSUM for change point detection.

This repo assists in building streaming analytics platform using RisingWave and dbt, empowering your real-time data insights.

Real-time ETL pipeline for financial data (kafka, pyspark) .

Autonomous Agent HyperLogLog (HLL) Probabilistic Distinct Elements Cardinality Estimator

Autonomous Agent HyperLogLog (HLL) Probabilistic Distinct Elements Cardinality Estimator

Misra-Gries frequency estimation algorithm identifying top-K frequent elements (heavy hitters) in high-velocity streaming data.

The detection engine: correlation rules on the event stream you already forward, outside the SIEM. Sequences across hosts in log time, state that survives a crash. Rust, no JVM, embeddable.

Extends the standard cumulocity administration with dialog to add analytics builder extensions

Misra-Gries frequency estimation algorithm identifying top-K frequent elements (heavy hitters) in high-velocity streaming data.

⚡ Real-time fraud & anomaly detection system for streaming transactions. Built with Kafka Streams + Isolation Forest ML. Low-latency processing, online learning, and scalable architecture for detecting fraud patterns in transaction data. 🚨🔍

Online, interpretable anomaly detection for industrial sensor streams — self-adapting operating limits, root-cause isolation, no labels or retraining.

Sub-second OLAP serving over a live event stream: ClickHouse incremental materialised views keep rollups fresh at insert time — no batch job. FastAPI + chDB/server.

This repo provides a template for developing Cumulocity Streaming Analytics assets such as Blocks and EPL Apps, with a dev container for opening in Visual Studio Code

Real-time monitoring pipeline using Kafka, Flink, PostgreSQL, and Grafana to stream metrics, detect anomalies (EWMA + 3σ), and visualize results.