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Top 25 Use Cases of Cloudera Flow Management Powered by Apache NiFi

Top 25 Use Cases of Cloudera Flow Management Powered by Apache NiFi

 Cloudera Flow Management has proven immensely popular in solving so many different use cases I thought I would make a list of the top twenty-five that I have seen recently.   

If you have never used CFM or Apache NiFi before, please checkout these two quick resources: and


25.   Ingesting Data into Kafka in the Public Cloud

24.  Cybersecurity Data Collection and Filtering

23.  Ingesting Data into Hive in the Public Cloud

22. Ingesting Data into HBase in the Public Cloud

21. Ingesting Data into Kudu in the Public Cloud


20.  Ingesting Data into ADLS Storage

19.   Populate SOLR Indexes

18.  Hadoop Data to Kafka

17.   Deep Learning And Machine Learning Pipelines

16.  Intercepting JMS and SOA


15.    Edge ML Model Integration

14.   Migrate Data from On-Premise Private Cloud to Public Cloud

13.   Converting XML to JSON

12.   MQTT to HDFS

11.   Ingesting REST Endpoints (Bulk)


10.  Ingesting Data into AWS S3 Buckets

9.  Ingest REST Endpoints

8.  Ingesting SAAS Products Like Salesforce

7.   Automating Manual Tasks

6.  Ingesting Social Media Data

Top 5

5.  Logs, Logs, Logs

4.  FLaNK Streaming Data Pipeline (Any Data to Kafka to Flink SQL)

3.   IoT - MiNiFi Agents Ingest, Store and Forward

2. Pseudo-CDC / Database Ingest

1.  Doing a 1,000 different ingest, conversion, routing and transformation flows

The most common use case is doing a lot of things with a lot of data, including things like documents, XML, JSON, AVRO, Parquet, CSV, PDF, Images, Video, Mongo documents, Logs and more.    Rarely do I ever see someone solve just one problem with NiFi and say, that was enough.   One simple use cases leads to another and another and before you know it every cron job, script, ETL, ELT and big data op is now touched by NiFi.    Keep it up, Cloudera will make it ever easier soon.   Also check out NiFi Stateless for some of those more job/event oriented things like File to Kafka, Kafka to Kafka and more.

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