![]() Routing : Priority, dynamic/static, based on content or metadata etcĪpache Nifi provide documentation for every processor.Data enrichment: Attribute, content, rules etc.Transformation : ‐ Format conversion (JSON to Avro, CSV to ORC etc.) ‐ Compression/decompression, Merge, Split,encryption etc.Extraction (XML, JSON, Regex, Grok etc.).‐ Databases: JDBC, MongoDB, HBase, Cassandra etc. Ingestion: connectors to read/write data from/to several data sources ‐ Protocols: HTTP (S), AMQP, MQTT, UDP, TCP, CEF,JMS, (S) FTP, etc.What can be done with Apache Nifi processors ? To learn more about MINIFI follow this link : and data can be collected from a variety of protocols. MINIFI is used as an agent and we can applying primary features of NiFi at the earliest possible stage. It is a sub-project of Apache NiFi, MINIFI can bring data from sources directly to a central NiFi instance and it is able to run most of NiFi’s available processors. This input and outputs range from local files to cloud services to databases and everything in between, Apache Nifi is open-source and easily extendable, any processor not yet included can be created on the fly as per your own specifications, but for now here is the example provided by Nifi home page What is Apache MINIFI ? Here is a very small sample of a few different processors available to us in Nifi, i personally like to regroup them like this : Inputs, Outputs, and the transformations and flow logic that goes in between Time statistics gives you a brief window of the activity of that processor, useful in case more or less data is coming through than you thought The status is whether is that processor stopped, started or incorrectly configured. Both ways are suitable and depends upon requirements and scenarios.įor more details about Kafka you can follow this links : It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies.Īpache NiFi can work as a Producer and a Consumer for Kafka. It was given open source status and passed to the Apache Foundation - which coordinates and oversees development of open source software - in 2011.Īpache Kafka is used for building real-time data pipelines and streaming apps. Kafka was originally created at LinkedIn, where it played a part in analysing the connections between their millions of professional users in order to build networks between people. ![]() Apache KafkaĪpache Kafka is an open source, distributed streaming platform used to storing, reading and analysing streaming data. Sinks are basically the same as sources, but they are designed for writing data. If ready-made processor boxes are not enough, you can code on Python, Shell, Groovy, or even Spark for data transformation. Think Extract for sources, Transform for processors, and Load for sinks.’Īlmost anything can be a source, for example, files on the disk or AWS, JDBC query, Hadoop, web service, MQTT, RabbitMQ, Kafka, Twitter, or UDP socket.Ī processor can enhance, verify, filter, join, split, or adjust data. There are three main types of boxes: sources, processors, and sinks. You just use ready-made “processors” represented with boxes, connect them with arrows, which represent exchange of data between “processors,” and that’s it. ![]() Yes, you don’t have to know any programming language. Some of them are open source and some are suitable for ETLĮTL is short for extract, transform, load. With Dataflow Programming tools you can visually assemble programs from boxes and arrows, writing zero lines of code. Today, we have many of ETL and data integration software, Some of these solutions are not free and more expansive, and others are maintained and operated by a community of developers looking to democratize the process. Apache Nifi in real-Time Event Streaming with Kafka.Apache Nifi as Producer and Consumer Kafka.Build a first processor and data processing.How to install Apache Nifi on centos 7 ?.Introduction to Apache Nifi and Apache Kafka.
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