Demos and examples for the Feldera incremental compute engine.
All demos can be run inside Claude Code — install it first from https://claude.ai/code.
Open this repo in Claude Code:
claude .Claude handles all steps automatically: Feldera setup, pipeline loading, SQL generation, and live monitoring.
Note
If you want to run demos without the assistance of claude. Look into the
README.md of the individual demo folders.
| Demo | Folder | Claude Code Command | Interfaces with | Description |
|---|---|---|---|---|
| Agentic Fraud Detection | agentic-fraud-detection/ | /run_fraud_demo |
AI Agent (Claude) | Claude reads a real card-skimming attack report, maps signals to a live transaction pipeline, generates SQL detection views, and runs a live fraud investigator that classifies alerts in real time. |
| Agentic Fine-Grained Access | agentic-fine-grained-access/ | /run_fga_demo |
AI Agent (Claude) | Claude generates detection views for rapid enumeration and hot-folder attacks in a shared file system governed by recursive group permissions. A live investigator classifies flagged users and blocks SUSPICIOUS ones by pushing is_banned=true — Feldera revokes their access within milliseconds. |
| Fraud Detection (Delta Lake) | fraud-detection-delta-lake/ | /run_fraud_delta_lake |
Delta Lake, S3, XGBoost | Batch fraud detection reading from Delta Lake tables on S3, with XGBoost model training. |
| Debezium + Postgres | debezium-postgres/ | /run_debezium_postgres |
Postgres, Debezium, Redpanda/Kafka | CDC pipeline ingesting Postgres changes via Debezium and Redpanda/Kafka. |
| Debezium + MySQL | debezium-mysql/ | /run_debezium_mysql |
MySQL, Debezium, Redpanda/Kafka | CDC pipeline ingesting MySQL changes via Debezium and Redpanda/Kafka. |
| Debezium + JDBC | debezium-jdbc/ | /run_debezium_jdbc |
Postgres, Debezium, Redpanda/Kafka | CDC pipeline sinking Feldera views to Postgres via Redpanda/Kafka and JDBC sink connectors. |
| Hopsworks Integration | hopsworks/ | /run_hopsworks |
Hopsworks, Kafka, XGBoost | Feature pipeline integration with Hopsworks feature store and Kafka, with XGBoost model training. |
| TikTok Recommender System | tik-tok-recommender-system/ | /run_tiktok |
Redpanda/Kafka | TikTok-style recommendation system using Feldera and Redpanda/Kafka. |
For a smooth experience, the following dependencies should be setup.
Feldera instance: You can use feldera using the free feldera online sandbox or a local setup using docker. claude will
| Option | How |
|---|---|
| Remote instance (e.g. try.feldera.com) | Add FELDERA_HOST=https://... and FELDERA_API_KEY=apikey:... to .env |
| Docker (no account needed) | Leave .env as-is — Claude pulls and starts the container, docker or podman is required to be installed |
Note that demos which rely on docker compose scripts to setup 3rd party services (postgres, mysql, kafka/redpanda) will only work with the local docker form factor.
Some demos use the fda CLI to interact with feldera. You can find instructions to install it in our docs.
curl -fsSL https://feldera.com/install-fda | bash
Some demos use pythons scripts and the feldera python SDK to interact with feldera. For this a recent installation of uv is necessary.