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What is dbForge Unit Test?

dbForge Unit Tests for SQL Server is a user-friendly graphical interface tool that acts as an add-in for SQL Server Management Studio (SSMS). Utilizing the tSQLt framework, it enables developers to create unit tests in T-SQL directly within the SSMS environment they are accustomed to. Notable Features: - Isolated Unit Testing: Safeguards the actual database from unintended changes. - Simultaneous Testing: Conduct multiple unit tests at the same time. - DevOps Integration: Seamlessly incorporate unit tests into DevOps workflows. - Command Line Execution: Execute unit tests through the command line interface. - T-SQL-based: Allows developers to write unit tests in T-SQL without needing extra tools. - tSQLt Framework Management: Simplifies the installation and uninstallation of the tSQLt framework for unit test creation. - Example Collection: Provides access to a variety of unit test examples for quick and efficient execution of standard tasks. - Safe Refactoring: Supports safe refactoring processes even in extensive databases. Furthermore, the tool features a Test List Manager, which is a dedicated tab in the SSMS interface designed for the creation, editing, management, and execution of unit tests, ensuring that teams can operate entirely within SSMS. This integration minimizes the need for switching between different applications, thus creating a more streamlined and productive working atmosphere. Additionally, it enhances collaboration among team members by maintaining consistency in the testing process.

What is Deequ?

Deequ is a groundbreaking library designed to enhance Apache Spark by enabling "unit tests for data," which helps evaluate the quality of large datasets. User feedback and contributions are highly encouraged as we strive to improve the library. The operation of Deequ requires Java 8, and it is crucial to recognize that version 2.x of Deequ is only compatible with Spark 3.1, creating a dependency between the two. Users of older Spark versions should opt for Deequ 1.x, which is available in the legacy-spark-3.0 branch. Moreover, we also provide legacy releases that support Apache Spark versions from 2.2.x to 3.0.x. The Spark versions 2.2.x and 2.3.x utilize Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases rely on Scala 2.12. Deequ's main objective is to conduct "unit-testing" on data to pinpoint possible issues at an early stage, thereby ensuring that mistakes are rectified before the data is utilized by consuming systems or machine learning algorithms. In the upcoming sections, we will illustrate a straightforward example that showcases the essential features of our library, emphasizing its user-friendly nature and its role in preserving data quality. This example will also reveal how Deequ can simplify the process of maintaining high standards in data management.

Media

Media

Integrations Supported

Apache Spark
SQL
SQL Server
SQL Server Management Studio (SSMS)

Integrations Supported

Apache Spark
SQL
SQL Server
SQL Server Management Studio (SSMS)

API Availability

Has API

API Availability

Has API

Pricing Information

$169.95
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Devart

Date Founded

1997

Company Location

United States of America

Company Website

www.devart.com

Company Facts

Organization Name

Deequ

Company Website

github.com/awslabs/deequ

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Categories and Features

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