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Description
Apache Ivy™ serves as a widely-used dependency manager that emphasizes both flexibility and ease of use. Discover its distinct enterprise capabilities, user feedback, and the ways it can enhance your build process! Ivy operates as a tool designed for the management of project dependencies, which includes recording, tracking, resolving, and reporting. It is not confined to any specific methodology or framework, allowing it to be highly adaptable to various dependency management and build workflows. Although it can function independently, Ivy is particularly effective in conjunction with Apache Ant, offering a variety of robust Ant tasks that range from resolving dependencies to generating reports and facilitating publication. Among its many powerful attributes, users often highlight its flexibility, seamless integration with Ant, and an efficient engine for managing transitive dependencies. Additionally, Ivy is an open-source tool, distributed under a permissive Apache License, making it accessible for a wide audience. This combination of features positions Ivy as a valuable asset for developers seeking to streamline their dependency management processes.
Description
Deequ is an innovative library that extends Apache Spark to create "unit tests for data," aiming to assess the quality of extensive datasets. We welcome any feedback and contributions from users. The library requires Java 8 for operation. It is important to note that Deequ version 2.x is compatible exclusively with Spark 3.1, and the two are interdependent. For those using earlier versions of Spark, the Deequ 1.x version should be utilized, which is maintained in the legacy-spark-3.0 branch. Additionally, we offer legacy releases that work with Apache Spark versions ranging from 2.2.x to 3.0.x. The Spark releases 2.2.x and 2.3.x are built on Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases require Scala 2.12. The primary goal of Deequ is to perform "unit-testing" on data to identify potential issues early on, ensuring that errors are caught before the data reaches consuming systems or machine learning models. In the sections that follow, we will provide a simple example to demonstrate the fundamental functionalities of our library, highlighting its ease of use and effectiveness in maintaining data integrity.
API Access
Has API
No
API Access
Has API
No
Integrations
Apache Ant
Yes
Apache Spark
No
JFrog
Yes
Perforce TeamHub
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
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
Country
United States
Website
ant.apache.org/ivy/
Vendor Details
Company Name
Deequ
Website
github.com/awslabs/deequ