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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

A user-friendly, robust, and dependable system for data processing and distribution is offered by Apache NiFi, which facilitates the creation of efficient and scalable directed graphs for routing, transforming, and mediating data. Among its various high-level functions and goals, Apache NiFi provides a web-based user interface that ensures an uninterrupted experience for design, control, feedback, and monitoring. It is designed to be highly configurable, loss-tolerant, and capable of low latency and high throughput, while also allowing for dynamic prioritization of data flows. Additionally, users can alter the flow in real-time, manage back pressure, and trace data provenance from start to finish, as it is built with extensibility in mind. You can also develop custom processors and more, which fosters rapid development and thorough testing. Security features are robust, including SSL, SSH, HTTPS, and content encryption, among others. The system supports multi-tenant authorization along with internal policy and authorization management. Also, NiFi consists of various web applications, such as a web UI, web API, documentation, and custom user interfaces, necessitating the configuration of your mapping to the root path for optimal functionality. This flexibility and range of features make Apache NiFi an essential tool for modern data workflows.

Description

Spark Streaming extends the capabilities of Apache Spark by integrating its language-based API for stream processing, allowing you to create streaming applications in the same manner as batch applications. This powerful tool is compatible with Java, Scala, and Python. One of its key features is the automatic recovery of lost work and operator state, such as sliding windows, without requiring additional code from the user. By leveraging the Spark framework, Spark Streaming enables the reuse of the same code for batch processes, facilitates the joining of streams with historical data, and supports ad-hoc queries on the stream's state. This makes it possible to develop robust interactive applications rather than merely focusing on analytics. Spark Streaming is an integral component of Apache Spark, benefiting from regular testing and updates with each new release of Spark. Users can deploy Spark Streaming in various environments, including Spark's standalone cluster mode and other compatible cluster resource managers, and it even offers a local mode for development purposes. For production environments, Spark Streaming ensures high availability by utilizing ZooKeeper and HDFS, providing a reliable framework for real-time data processing. This combination of features makes Spark Streaming an essential tool for developers looking to harness the power of real-time analytics efficiently.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

PubSub+ Platform Yes 
Acryl Data Yes 
Apache Kudu Yes 
Apache Spark No 
CrateDB Yes 
Data Flow Manager Yes 
DataHub Yes 
Datavolo Yes 
Kyrah Yes 
NXLog Yes 
OpenMetadata Yes 
Secberus Yes 
Stackable Yes 
ThinkData Works Yes 
Warp 10 Yes 

Integrations

PubSub+ Platform Yes 
Acryl Data No 
Apache Kudu No 
Apache Spark Yes 
CrateDB No 
Data Flow Manager No 
DataHub No 
Datavolo No 
Kyrah No 
NXLog No 
OpenMetadata No 
Secberus No 
Stackable No 
ThinkData Works No 
Warp 10 No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

nifi.apache.org

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org/streaming/

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