What is Apache NiFi?
An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
Apache NiFi is a tool in the Message Queue category of a tech stack.
Who uses Apache NiFi?
12 companies reportedly use Apache NiFi in their tech stacks, including Hepsiburada, Wongnai, and PlacePass.
43 developers on StackShare have stated that they use Apache NiFi.
Apache NiFi Integrations
MongoDB, Amazon S3, Kafka, Amazon SQS, and Amazon SNS are some of the popular tools that integrate with Apache NiFi. Here's a list of all 9 tools that integrate with Apache NiFi.
Why developers like Apache NiFi?
Here’s a list of reasons why companies and developers use Apache NiFi
Apache NiFi's Features
- Web-based user interface
- Highly configurable
- Data Provenance
- Designed for extension
Apache NiFi Alternatives & Comparisons
What are some alternatives to Apache NiFi?
See all alternatives
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.
An open source Java framework that focuses on making integration easier and more accessible to developers.
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.