Best Data Management Software for Mercurial

Compare the Top Data Management Software that integrates with Mercurial as of August 2025

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This a list of Data Management software that integrates with Mercurial. Use the filters on the left to add additional filters for products that have integrations with Mercurial. View the products that work with Mercurial in the table below.

What is Data Management Software for Mercurial?

Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security. Compare and read user reviews of the best Data Management software for Mercurial currently available using the table below. This list is updated regularly.

1

DataGrip

JetBrains

Meet DataGrip, our new database IDE that is tailored to suit the specific needs of professional SQL developers. Allows you to execute queries in different modes and provides a local history that keeps track of all your activity and protects you from losing your work. Lets you jump to any table, view, or procedure by its name via the corresponding action, or directly from its usages in the SQL code. Gives you an extended insight into how your queries work and into the database engine behavior, so you can make your queries more efficient. DataGrip provides context-sensitive code completion, helping you to write SQL code faster. Completion is aware of the tables structure, foreign keys, and even database objects created in code you're editing. DataGrip detects probable bugs in your code and suggests the best options to fix them on the fly. It will immediately let you know about unresolved objects, using keywords as identifiers and always offers a way to fix the problems.

2 Ratings

Starting Price: $199 per year

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2

dbForge Source Control

Devart

dbForge Source Control for SQL Server is a powerful add-in for SQL Server Management Studio (SSMS) that enables version control within the familiar interface. Key Features: - Wide support for source control systems (including Git (and GitHub), Perforce (P4), Mercurial, SourceGear Vault, Subversion (SVN), and others) - Simplified database linking to source control systems with dedicated wizards - Support for both shared and dedicated development workflows - Visual management of source control operations, such as committing changes, rolling back modifications, and resolving conflicts - Enhanced commit functions with comments and highlighting differences - Access to the history of changes The user-friendly interface of dbForge Source Control ensures quick adoption, improves processes, and supports database developers and managers in establishing effective DevOps practices for more efficient and accurate product delivery.

Starting Price: $189.95

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3

OpsHub

OpsHub

OpsHub Integration Manager (OIM) can be configured to synchronize data between any of the 50+ tools in the ALM ecosystem. OIM provides an easy-to-use interface and intuitive user experience allowing users to easily configure the integration. The platform is built to be resilient and guarantees consistency of data in the systems that are being integrated. Businesses with heterogeneous IT landscapes need an agile integration that can put their entire value stream on a fast track and be a partner in their digital transformation. To remain competitive in the ever-evolving digital economy, it is now more crucial than ever to optimize processes and keep each step through the process connected. With OpsHub, get an enterprise-class integration solution that has been transforming clients’ value stream for over two decades.

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4

GenRocket

GenRocket

Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.

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