Name: SQL Server
Rating: 4.5 (2562 reviews)

Overview

Product Information on SQL Server

Updated 13th October 2025

What is SQL Server?

SQL Server is a relational database management software developed to support data storage, retrieval, and management for organizations of varying sizes. The software enables users to securely store and access structured data, run queries, create reports, and perform analytics. It supports transaction processing, business intelligence, and analytics applications. The software includes tools for database administration, backup and recovery, security management, and automated maintenance. It offers integration with other applications and supports scalability to accommodate growing data needs. SQL Server aims to address challenges related to managing large volumes of data, ensuring data integrity, and enabling businesses to analyze information for operational and strategic decision-making.

Overall experience with SQL Server

SENIOR SRE

500M - 1B USD, IT Services

FAVORABLE

“Outstanding data masking tool!”

4.0

Jul 7, 2024

Microsoft sql server is a solid relational database product. It is continually being updated and best product for our data masking needs

SOFTWARE DEVELOPER

3B - 10B USD, Miscellaneous

CRITICAL

“Works well for monitoring large databases .”

3.0

May 13, 2023

This SQL server is basically made for managing large database system storage which is easy in design and efficient to handle large amount of data. This tool works very well on large enterprise level with secure features.

About Company

Company Description

Microsoft enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more. Microsoft is dedicated to advancing human and organizational achievement. Microsoft Security helps protect people and data against cyberthreats to give peace of mind.

Company Details

Company type

Public

Year Founded

1975

Head office location

Redmond, Washington, United States

Number of employees

10000+

Annual Revenue

30B+ USD

Website

https://microsoft.com

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Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

Reviewer Insights for: SQL Server

Deciding Factors: SQL Server Vs. Market Average

Performance of SQL Server Across Market Features

SQL Server Likes & Dislikes

expertise, advanced features, support

Microsoft SQL server includes set of development tools such as data analysis , data masking, data warehousing etc. in support of different different programming languages.

SQL is well suited handling large-datasets. Ease of implementation. Granular control. Flexibility.

The licensing fees are very high if you go with enterprise editions. Support can be hit or missed at times. sensitive Data should be identified first so we can implement correctly

This tool is little bit expensive for users with complex user interface .

Maintenance challenges. Steep learning curve.

Top SQL Server Alternatives

Peer Discussions

SQL Server Reviews and Ratings

Recommended Gartner Insights

Market Guide for Data Masking (Transitioning to Data Masking and Synthetic Data)

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IT Analyst

How are automated database builds handled for SQL Server through a build/release pipeline. What is the failback mechanism if there are failures during database update during both DDL and DML. Any specific tool recommendation would be helpful.

Information Security Manager

Automated database builds for SQL Server through a build/release pipeline are typically managed using tools that integrate with continuous integration (CI) and continuous deployment (CD) systems. Here's an overview of how this process is handled: ### 1. **Automated Database Build Process** - **Source Control:** The database schema (DDL) and scripts (DML) are stored in source control, often using tools like Git. This can include SQL scripts or projects created using Visual Studio (SQL Server Data Tools – SSDT) or other database tools. - **Build Pipeline:** - **Build Definition:** A build pipeline for SQL Server usually triggers automatically upon changes to the source repository. For instance, using tools like Azure DevOps, Jenkins, or TeamCity. - **Database Project/Schema Validation:** The pipeline uses tools like **SSDT** (SQL Server Data Tools), **Redgate SQL Change Automation**, or **Flyway** to validate and compile database projects. This ensures that the DDL is valid and ready for deployment. - **Unit Tests for Database:** You can integrate database unit testing using tSQLt or other frameworks to ensure the new changes do not break the database. ### 2. **Database Release Process** - **Release Pipeline:** - The release process often consists of deploying the new DDL and DML changes to different environments (Dev, QA, Staging, and Production). - Tools like **Redgate SQL Change Automation**, **Liquibase**, **Flyway**, or **DbUp** manage schema changes and migrations by applying incremental changesets, tracking the history of changes, and ensuring consistency across environments. - **Rollback/Fallback Mechanism:** - **Transaction Management:** During deployment, SQL scripts can be wrapped in transactions. If a failure occurs, the transaction is rolled back. - **Backup Mechanism:** - Before deployment, a full or differential database backup is often taken to enable a complete rollback if a critical failure occurs. - **Schema Versioning and Rollbacks:** Tools like Flyway, Redgate SQL Change Automation, or Liquibase maintain a version history of database migrations. These tools allow rollback to a previous version in case of failure. - Flyway, for example, has a `migrate` and `undo` feature, and Redgate provides a schema comparison to reverse changes. - **Rolling Back DDL Changes:** If a DDL (e.g., table alterations) fails, reverting to the previous schema version can be handled by the version control tool, though this is complex and requires careful planning. - **Rolling Back DML Changes:** For DML changes (e.g., data modification), compensating transactions or rollback scripts can be included to reverse any data modifications made in case of a failure. ### 3. **Handling Failures (DDL & DML)** - **DDL Failures (Schema Changes):** - Use **schema comparison tools** like **Redgate SQL Compare** or SSDT to identify and rollback changes if failures occur. - **Transactional Deployment**: If possible, wrap schema changes in a transaction and roll back the transaction upon failure. - In case of failure, either restore from a backup or use the rollback feature of tools like Liquibase or Flyway. - **DML Failures (Data Modifications):** - Include rollback scripts or compensating transactions to undo data changes in case of errors. - **Pre-checks:** Always run validation queries (e.g., SELECT statements) before applying DML to ensure the data consistency is maintained. - Use backup and restore techniques or employ log shipping to revert databases to a known good state if failures occur during DML changes. ### 4. **Tool Recommendations** - **Redgate SQL Change Automation:** Excellent for automating deployments and managing schema changes with a focus on safety and rollback mechanisms. It integrates well with Azure DevOps, Jenkins, and other CI/CD tools. - **Flyway:** A powerful open-source tool for database migrations with support for SQL Server. It handles versioned migrations (DDL and DML) and has rollback (`undo`) support. - **Liquibase:** Similar to Flyway, Liquibase tracks database schema changes and supports rollbacks. It integrates with various CI/CD pipelines. - **Azure DevOps Pipelines:** Native support for SQL Server database builds and deployments, integrates well with SSDT and Redgate tools. - **DbUp:** A lightweight .NET-based tool for managing database migrations. It's simple and easy to integrate into build pipelines. ### Best Practices: - Always use transactional DDL and DML scripts to ensure you can roll back in case of failures. - Implement automated database backups before applying updates. - Test deployments in staging environments thoroughly before pushing to production. - Ensure that all migrations and rollback scripts are version-controlled. This combination of tools and techniques ensures a robust, automated process for building, releasing, and rolling back changes in SQL Server databases.

See Full Discussion

19 Sep 2024610 Views1 Comment

50M-1B USD

IT Services

Review Source

Outstanding data masking tool!

Associate

10B+ USD

Finance (non-banking)

SQL Server for Data Masking

Mar 1, 2024

SQL helps in masking sensitive information while leaving other data untouched. SQL based data masking ensures consistent application of masking rules across various database operations, maintaining integrity and coherence. SQL based data masking operations are inherently auditable, which helps in providing a clear trail of the applied masking rules and changes, aiding in compliance and security assessments.

RESEARCHER

Gov't/PS/Ed

Education

Microsoft SQL Server is a perfect blend of performance and security.

5.0

May 11, 2023

Microsoft SQL Server is a powerful RDBMS that offers business analytics and high transaction processing with high efficiency. This database is very easy to install and requires only 1 GB of memory to start with.

Microsoft SQL Data Masking Is Providing You A Solution For Masking On Sensitive Data

May 16, 2023

Overall Of My Experience, Microsoft SQL Data Masking Is Providing A Solution For Preventing Unauthorized Access To Sensitvie Information By Replacing Original Data With Realistic But Fictitious Data.

Healthcare and Biotech

Review about Microsoft SQL Server

May 29, 2023

Sql stands its mark in our organization for data privacy and masking