Apache NiFi Overview
A Powerful Data Integration & Automation Tool
What is Apache NiFi?
• • Open-source data integration & automation tool
• • Web-based drag-and-drop UI for designing data flows
• • Moves, transforms, and processes data in real time
• • Supports multiple data sources and destinations
Key Features of Apache NiFi
• ✅ Real-Time Data Flow: Stream & batch processing
• ✅ Drag-and-Drop UI: Easy-to-use, no coding required
• ✅ Supports Various Data Sources: Databases, APIs, IoT, Files, etc.
• ✅ Scalability: Single-node or clustered deployment
• ✅ Security & Governance: Authentication, encryption, data tracking
• ✅ Extensibility: Custom processors and integrations
Common Use Cases
• 🔹 Data Warehousing: ETL for Snowflake, Redshift, BigQuery
• 🔹 IoT Data Processing: Real-time sensor data collection
• 🔹 Log and Event Processing: Aggregating logs for analytics
• 🔹 Cloud Data Migration: Moving data between on-premises &
cloud
• 🔹 Big Data Integration: Ingesting data into Hadoop, Spark, etc.
Nifi Flow Diagram

Overview of NiFi Product by Apache Foundation

  • 1.
    Apache NiFi Overview APowerful Data Integration & Automation Tool
  • 2.
    What is ApacheNiFi? • • Open-source data integration & automation tool • • Web-based drag-and-drop UI for designing data flows • • Moves, transforms, and processes data in real time • • Supports multiple data sources and destinations
  • 3.
    Key Features ofApache NiFi • ✅ Real-Time Data Flow: Stream & batch processing • ✅ Drag-and-Drop UI: Easy-to-use, no coding required • ✅ Supports Various Data Sources: Databases, APIs, IoT, Files, etc. • ✅ Scalability: Single-node or clustered deployment • ✅ Security & Governance: Authentication, encryption, data tracking • ✅ Extensibility: Custom processors and integrations
  • 4.
    Common Use Cases •🔹 Data Warehousing: ETL for Snowflake, Redshift, BigQuery • 🔹 IoT Data Processing: Real-time sensor data collection • 🔹 Log and Event Processing: Aggregating logs for analytics • 🔹 Cloud Data Migration: Moving data between on-premises & cloud • 🔹 Big Data Integration: Ingesting data into Hadoop, Spark, etc.
  • 5.