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streaming-data

Build event streaming pipelines across Kafka, Pulsar, Redpanda, Flink, and Spark.

1|Updated Apr 8, 2026
Search Tags:#patterns#real-time#streaming#kafka#event-sourcing#cdc#pulsar
One-click install
npx skills add https://github.com/masermediagroup-stack/CursorSkills --skill streaming-data-masermediagroup-stack
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: streaming-data
Source: https://github.com/masermediagroup-stack/CursorSkills/tree/main/skills-bundle/skills/community/ai-design-components/skills/streaming-data
Command: npx skills add https://github.com/masermediagroup-stack/CursorSkills --skill streaming-data-masermediagroup-stack

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build end-to-end event streaming and real-time data pipelines across Kafka, Pulsar, Redpanda, Flink, and Spark. This Skill coordinates multiple brokers, languages, and processors to reduce integration complexity and operational overhead.

Core Features & Use Cases

  • Producer/consumer patterns across Kafka, Pulsar, Redpanda
  • Stream processing, event sourcing, and CDC with Flink, Spark, and Kafka Streams
  • Multi-language support (TypeScript, Python, Go, Java) for real-time apps
  • Use cases include real-time analytics, microservices data flows, and IoT data ingestion

Quick Start

Create a basic producer and consumer in your language of choice to stream a small set of events through Kafka or Pulsar.

Frequently Asked Questions about streaming-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a real-time data pipeline with Kafka or Pulsar?▼

You can build a real-time data pipeline by implementing producer and consumer patterns across Kafka, Pulsar, or Redpanda. This Skill supports stream processing, event sourcing, and CDC using multi-language SDKs.

What is event sourcing and CDC in stream processing?▼

Event sourcing and Change Data Capture (CDC) are streaming patterns supported here through Flink, Spark, and Kafka Streams. They enable capturing data changes and applying stream processing for real-time analytics and microservices data flows.

Can I implement stream processing across different programming languages?▼

Yes, you can implement stream processing across TypeScript, Python, Go, and Java. The Skill provides multi-language SDKs to enable real-time apps, microservices data flows, and IoT data ingestion across different brokers.

Does this approach work with both Flink and Spark for real-time analytics?▼

Yes, real-time analytics are supported through both Flink and Spark. The Skill coordinates these processors alongside brokers like Kafka and Pulsar to handle stream processing and reduce operational overhead.

What's the best way to coordinate multiple brokers for event streaming?▼

The best way to coordinate multiple brokers for event streaming is using a unified approach that manages Kafka, Pulsar, and Redpanda together. This reduces integration complexity and operational overhead across your data pipelines.

Why use CDC for microservices data flows instead of batch processing?▼

Using CDC for microservices data flows enables real-time data integration by capturing row-level changes. This Skill applies CDC and event sourcing to ensure data consistency across services without the latency of batch processing.

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