Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Nussknacker allows domain experts to use a visual tool that is low-code to help them create and execute real-time decisioning algorithm instead of writing code.
It is used to perform real-time actions on data: real-time marketing and fraud detection, Internet of Things customer 360, Machine Learning inferring, and Internet of Things customer 360.
A visual design tool for decision algorithm is an essential part of Nussknacker.
It allows non-technical users, such as analysts or business people, to define decision logic in a clear, concise, and easy-to-follow manner. With a click, scenarios can be deployed for execution once they have been created. They can be modified and redeployed whenever there is a need.
Nussknacker supports streaming and request-response processing modes. It uses Kafka as its primary interface in streaming mode. It supports both stateful processing and stateless processing.
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
No
API Access
Has API
No
Integrations
Apache Spark
No
PubSub+ Platform
No
Pricing Details
0
open source with enterprise extensions
Free Trial
Yes
Free Version
Yes
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
Nussknacker
Website
nussknacker.io
Vendor Details
Company Name
Apache Software Foundation
Founded
1999
Country
United States
Website
spark.apache.org/streaming/
Product Features
Low-Code Development
AI-Assisted Development
No
Business Process Automation
Yes
Collaborative Development
No
Data Aggregation and Publishing
No
Deployment Management
Yes
Drag & Drop
Yes
Integrations Management
No
Iteration Management
No
Performance Monitoring
Yes
Requirements Management
No
Templates
No
Visual Modeling
No
Web / Mobile App Development
No
Workflow Management
No