MongoDB Atlas
MongoDB Atlas stands out as the leading cloud database service available, offering unparalleled data distribution and seamless mobility across all major platforms, including AWS, Azure, and Google Cloud. Its built-in automation tools enhance resource management and workload optimization, making it the go-to choice for modern application deployment. As a fully managed service, it ensures best-in-class automation and adheres to established practices that support high availability, scalability, and compliance with stringent data security and privacy regulations. Furthermore, MongoDB Atlas provides robust security controls tailored for your data needs, allowing for the integration of enterprise-grade features that align with existing security protocols and compliance measures. With preconfigured elements for authentication, authorization, and encryption, you can rest assured that your data remains secure and protected at all times. Ultimately, MongoDB Atlas not only simplifies deployment and scaling in the cloud but also fortifies your data with comprehensive security features that adapt to evolving requirements.
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Google Cloud SQL
Cloud SQL is a fully managed relational database service that supports MySQL, PostgreSQL, and SQL Server. It includes rich extensions, configuration flags, and developer ecosystems. Cloud SQL offers $300 in credits for new customers. You won't pay until you upgrade. Reduce maintenance costs by using fully managed MySQL, PostgreSQL, and SQL Server databases. The SRE team provides 24/7 support for reliable and secure services. Data encryption in transit and at rest ensures the highest level of security. Private connectivity with Virtual Private Cloud, user-controlled network access, and firewall protection add an additional layer of safety.
Compliant with SSAE 16, ISO 27001, PCI DSS, and HIPAA, you can trust your data to be protected. Scale your database instances with a single API request, whether you are just testing or need a highly available database in production. Standard connection drivers and integrated migration tools let you create and connect to a database in a matter of minutes.
Transform your database management with AI-driven support in Gemini, currently available in preview on Cloud SQL. It enhances development, optimizes performance, and simplifies fleet management, governance, and migration.
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Ariga
Articulate the desired structure of your database using a straightforward and declarative format. Our open-source engine is capable of automatically creating migration plans that are validated during your team's established CI pipeline and subsequently deployed to production with confidence. Our platform meticulously simulates and evaluates every suggested modification throughout your existing CI process, ensuring that no inadvertent disruptions occur within the database. Identify potentially harmful changes, issues with backward compatibility, unintentional table locks, and constraint violations long before they make their way into production environments. Implement database schema alterations seamlessly within your continuous delivery pipelines through our integrations with Terraform or Helm. Additionally, our platform empowers you to execute modifications that may not be entirely verifiable during CI, as they rely on the specific data present in the target database. This capability enhances the overall safety and reliability of your database management practices.
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Liquibase
One area that has not benefited as much from DevOps is the database change process. It is time to bring CI/CD into the database. In the last few years, application release technology has advanced significantly. It used to take weeks, if not months, to release new software. Organizations have changed their workflows and processes so that it takes just days or even hours to release new software. Every software project must perform database schema migrations. There are many reasons why database updates are necessary. New features may require the addition of new attributes to existing tables, or completely new tables. Bug fixes can lead to changes in the names and data types of the database. Additional indexes may be required to address performance issues. Manual rework is still common in DevOps-adopted organizations when it comes to stored procedure and database schema changes.
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