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Cascading
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Cascading

Overview
Synopsis

Cascading is a proven application development platform for building Big Data applications on Apache Hadoop. Whether solving simple or complex data problems, Cascading balances an optimal level of abstraction with the necessary degrees of freedom through a computation engine, systems integration framework, data processing and scheduling capabilities.

Category

ETL Software Free

Features

Java API
Data Processing API
Data Integration API
Scheduler API
Query Process Planner

License

Proprietary Software

Price

Contact for Pricing

Pricing

Subscription

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

Website
Company

Cascading

What is best?

Taps and Schemes
Portable
Test-Driven
Reduced operational complexity

What are the benefits?

Quickly build robust, reliable, data-oriented applications in Java
Eliminate platform lock-in
Develop testable and reusable integrations, data processing code and algorithms

PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
8.6
8.7
Features & Functionality
8.4
9.1
Advanced Features
8.4
9.1
Integration
8.5
8.3
Performance
8.6
7.8
Customer Support
8.5
8.4
Implementation
8.1
Renew & Recommend
7.9
Bottom Line

Cascading offers Hadoop development teams portability. As new, more interesting, compute fabrics are developed, teams will need the ability to move existing applications without incurring the cost to rewrite them.

8.5
Editor Rating
8.4
Aggregated User Rating
2 ratings
You have rated this

Cascading is a proven application development platform for building Big Data applications on Apache Hadoop. Whether solving simple or complex data problems, Cascading balances an optimal level of abstraction with the necessary degrees of freedom through a computation engine, systems integration framework, data processing and scheduling capabilities.

Uniquely, the platform offers Hadoop development teams portability. As new, more interesting, compute fabrics are developed, teams will need the ability to move existing applications without incurring the cost to rewrite them.

With Cascading, it is simply a matter of changing a few lines of code and a Cascading application is ported to another supported compute fabric. Today, Cascading applications run on and can be ported between MapReduce, Apache Tez and Apache Flink.With Cascading, developers can build and test their application locally, and then deploy them at scale in production.

The underlying query planner accounts for scale so that the applications will run properly even when encountering large data sets or small clusters. The platform allows developers to efficiently test code and process local files before deploying them on a cluster with Cascading’s local or in-memory mode. It also enables them to incorporate inline data assertions to define results at any point in their pipeline, where failed assertions are available for analysis.

The platform also offers users many benefits, and some of them are listed below as follows: Quick building of robust, reliable, data-oriented applications, Elimination of compute fabric lock-in, Development of testable and reusable integrations, data processing code and algorithms and Leveraging of existing best practices, skill sets and tools.

You may like to read: Top Extract, Transform, and Load, ETL Software, How to Select the Best ETL Software for Your Business and Top Guidelines for a Successful Business Intelligence Strategy

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Ease of use
Features & Functionality
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Customer Support
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