Use of NiFi Product by Apache Foundation
- 1. Apache NiFi Use Cases A Powerful Data Integration & Automation Tool
- 2. 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.
- 4. Feature Apache NiFi Apache Airflow Primary Purpose Data flow management and ETL Workflow orchestration and scheduling Use Case Streaming and batch data movement Task scheduling and pipeline execution Architecture Flow-based, event- driven DAG (Directed Acyclic Graph) execution Data Handling Processes real-time streaming data Handles batch jobs (mostly) UI & Ease of Use User-friendly UI for designing flows Requires Python scripting for DAGs Integration Supports various data sources (HDFS, Kafka, DBs, APIs) Strong integration with cloud and DB services Scalability Scales horizontally with NiFi clusters Scales well with Celery Executors Fault Tolerance Built-in data lineage and retry mechanisms Task retries, but not as strong in real-time recovery State Management Persistent state tracking for flow files Stateless DAG execution Extensibility Custom processors (Java-based) Custom operators (Python-based) Real-time ETL, data NIFI Vs Airflow