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What is dbForge Schema Compare for SQL Server?

dbForge Schema Compare for SQL Server is a powerful utility tailored for the comparison and synchronization of schemas within SQL Server databases. It accommodates various data sources, including live databases, snapshots, and native backups, effectively pinpointing all schema discrepancies. These differences are presented in a visually appealing and informative interface, allowing users to promptly synchronize changes in either a comprehensive or selective manner, which can then be deployed to compatible platforms. Notable Features: - User-friendly task setup facilitated by intuitive wizards - Detection of alterations between development, staging, and production databases - Ability to recover missing or corrupted schema objects from native backups - Implementation of changes across SQL Server, SQL Azure, and SQL Server on Amazon RDS - Creation of schema synchronization scripts for immediate execution or future application - Capability to automate routine schema synchronization tasks using the command line Moreover, dbForge Schema Compare for SQL Server seamlessly integrates with SQL Server Management Studio (SSMS), enhancing the workflow for database developers and administrators, while its interface provides a familiar setting that eases the transition for users. This makes it an essential tool for maintaining database integrity and efficiency.

What is DataForge?

DataForge is unique as the only framework that integrates all three essential aspects of data development. By combining distinct features from each element and applying a thorough methodology, it creates an unmatched foundation for effective data design. Its cloud version, DataForge Cloud (DFC), acts as a powerful management service for data platforms, intricately aligned with the DataForge framework. DFC streamlines this framework into efficient automated workflows for developers, enabling data processing on platforms like Databricks and Snowflake. With a combination of structured coding and an event-driven workflow engine, DFC guarantees full automation in establishing necessary processing steps and overseeing dependencies. This standardization of processing phases promotes consistent infrastructure sizing, which boosts efficiency. Furthermore, DFC enhances performance through the dynamic allocation of resources, selecting the best cluster or warehouse at each stage to ensure optimal cost-effectiveness without compromising quality. This innovative strategy not only simplifies the development workflow but also substantially improves the overall user experience, making data management more accessible and efficient for all users. Overall, DataForge and DFC represent a significant advancement in the realm of data development and management.

Media

Media

Integrations Supported

Databricks Data Intelligence Platform
SQL
SQL Server
SQL Server Management Studio (SSMS)
Snowflake

Integrations Supported

Databricks Data Intelligence Platform
SQL
SQL Server
SQL Server Management Studio (SSMS)
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

$219.95
Free Trial Offered?
Free Version

Pricing Information

$2.50 per process
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

Czech Republic

Company Website

www.devart.com

Company Facts

Organization Name

DataForge

Date Founded

2023

Company Location

United State

Company Website

www.dataforgelabs.com

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

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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