Close the Velocity Gap with Database DevOps

Modern software and data delivery are broken. With the ever increasing pace of application delivery, organizations are automating processes to keep up. But database change remains manual, disconnected, and risky. This creates a Velocity Gap for companies struggling to accelerate delivery while increasing control. These challenges have become even more acute with the rise of AI and the ever increasing need for modern data products.

According to The State of Database DevOps Report 2025, organizations in the early stages of DevOps practices overwhelmingly cited data pipelines and AI/ML workloads as their top database management challenge, with 78% reporting it as the single biggest hurdle to overcome. On the other hand, just 44% of organizations running mature DevOps practices reported these to be major challenges.

“Mature teams are realizing more gains by implementing automation, allowing them to move faster, with fewer manual tasks and wait states. Database change management is being woven into CI/CD processes and the database is finally keeping pace with the application. Using automation at every level of the delivery chain is essential to closing the Velocity Gap.” - Pete Pickerill, Co-founder & Head of Developer Relations, Liquibase.

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Where Delivery Breaks: The Risk of Slow, Siloed Change

Organizations experiencing a Velocity Gap see it manifest in a number of ways across the software delivery chain. Manual changes create friction in delivery resulting in longer backlogs, production delays, and slower time-to-market. Delays in delivery result in loss of competitive advantage, slower time to market, lower rates of innovation, and ultimately reduced revenue. Here’s a snapshot of how these breakdowns negatively impact business:

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AI and the new tipping point for Database DevOps

Database DevOps has been an aspiration for years. What is changing is the market pressure at AI, machine learning, and an increasingly interconnected pattern of software delivery pressure organizations to accelerate. AI-powered apps and modern data products cannot tolerate manual, disconnected database change. Delivery must be fast, trusted, and governed across the stack.

Database DevOps is the extension of DevOps principles, technology, and processes to the database management workflow–eliminating a key bottleneck in the software delivery process. It operates under four core pillars:

1. Version control for database schema
2. Automated testing
3. Continuous integration
4. Deployment automation for database changes 

Unlike application code, databases contain valuable data often powering multiple applications and processes. This leads many organizations to view the DB as untouchable, allowing only the most senior engineers to make changes.

However, by treating database code like application code and leveraging similar tools and capabilities to create a more methodical, mechanized approach to change management, teams can ensure that updates to databases march in lockstep with software delivery, making the lifecycle smoother, faster, and more synchronized.

The results of applying Database DevOps speak for themselves. According to The State of Database DevOps Report 2025, 53% reduced manual workload for database administrators (DBAs) and developers, and 48% reported faster development cycles by implementing DevOps practices as part of database change management workflows.

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Developer velocity in practice

Software development is a highly demanding role, frequently made harder by poor cross-team communication and unnecessary manual processes which stall software releases. To increase productivity, developers should be able to rapidly and confidently implement features without waiting for database-related approvals or manual processes.

Key metrics of developer productivity include: 

Deployment Frequency
How often code is deployed to production. A higher deployment frequency indicates a faster delivery pipeline and a more responsive development team.

Mean Lead Time for Changes
The average time it takes for a code change to go from commit to deployment. A shorter lead time signals a more streamlined and efficient development process.

Mean Time to Recovery
The average time it takes to restore a system after a failure or service interruption. A faster MTTR demonstrates the resilience and stability of the system, and the efficiency of the incident response process.

Change Failure Rate
The percentage of code deployments that cause issues in production. A lower CFR indicates a more reliable deployment process and a higher quality codebase.

Leading organizations seeking to improve developer velocity use automation (standardized, repeatable workflows) to help improve this measurement. This shift has the added benefit of helping developers focus more time on value-creating work rather than debugging database deployment issues or waiting for database administrator (DBA) approvals.

According to Liquibase’s State of Database DevOps Report 2025, leading organizations are actively putting tooling in place to help achieve automation. Organizations running mature DevOps are more likely to automate checks for quality, security, and/or compliance (78%) compared to just 33% of organizations in the early stages of DevOps practices. Further, 56% of mature organizations leverage collaboration tools for DevOps and database teams, which only 33% of less mature businesses have adopted. 

Across all levels of maturity, organizations are actively putting tooling in place to help achieve greater productivity – 36% of respondents are leveraging database management tools, and 24% are applying version control integrated tools (e.g., Git-based schema management workflows). Meanwhile, 54% are using CI/CD database deployment automation, and 53% are leveraging version control for database schema changes, followed closely by database monitoring and observability tools (49%) as part of database change management workflows.

Leaders view these challenges differently and  measure developer productivity not only in technical metrics, but also in terms of business impact. Faster, more reliable delivery drives revenue, customer experience, and competitive advantage. Database DevOps is foundational to achieving these outcomes.

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Eliminate the Velocity Gap to Speed Delivery

For many organizations the database is the bottleneck in the delivery pipeline, significantly slowing down the overall speed of deployment–resulting in the Velocity Gap. With the explosion of artificial intelligence and machine learning, database change management is becoming more challenging than ever before. Organizations can use leading technologies like Liquibase Pro to close the Velocity Gap by choosing to:

Eliminate rework and needless maintenance: One common issue is the rework required for database changes, as modifications to schemas or data structures often need to be revisited or re-executed multiple times to ensure compatibility with application code. Limited version control for database schema exacerbates this problem, as it becomes difficult to track changes, roll back to previous versions, or collaborate effectively on database modifications. 

Increase transparency and controls to support developers as they improve testing and delivery: A lack of reliable testing environments that accurately mirror production databases leads to gaps in testing, making it harder to identify issues before deployment increasing the risk of post-release failures.

Implement transparency and eliminate silos: Compounding these issues, development and operations teams are accustomed to separate workflows and siloed communications, leading to the database being handled in a highly cautious, and far too often manual way.

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How Database DevOps solves productivity issues

Database DevOps tools, such as Liquibase Pro, are designed to significantly improve productivity by automating and governing database change management. This eliminates many of the manual, error-prone tasks that slow down development cycles but automation alone is not enough. Database DevOps also enforces governance and policy-driven control, ensuring that every change is safe, compliant, and aligned with business standards. This is critical for regulated industries and for AI-driven products where data quality and lineage matter. 

Leveraging Database DevOps tools, database changes are scripted, version-controlled, and deployed through CI/CD pipelines just like application code, ensuring seamless integration into the broader development process. 

Changes can be tested in isolation, as well as in integrated environments that mirror production, allowing for thorough validation before deployment. Self-service capabilities empower developers to safely make database changes without needing direct intervention from database administrators, which accelerates the development process while maintaining control and security. Plus standardized processes, backed by automation, ensure consistency across all environments—reducing the risk of discrepancies and errors. 

Additionally, Database DevOps promotes smaller, incremental changes instead of large, risky database scripts, which minimizes the likelihood of introducing significant issues and ensures that database updates are easier to manage, test, and roll back if necessary. 

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Implementing Database DevOps with Liquibase Pro

Modern software and data delivery are broken because change at the database layer still looks like it did 15–20 years ago.

Teams have automated everything else: application code, infrastructure, and data pipelines. With the rise of AI, development is only accelerating. But as speed increases, so does the need for governance, observability, and trust. The challenge is that database change is still stuck with manual reviews, tribal knowledge, and disconnected workflows. In reality, most teams are managing database change the same way they did in the early 2000s only now they’re surrounded by Kubernetes, Terraform, GitHub Actions, and Databricks.

Leading engineering and data teams choose Liquibase Pro to close the Velocity Gap and modernize delivery. From AI-driven startups to global enterprises, Liquibase powers fast, trusted, and governed database change across the stack.

Liquibase is not only one of the fastest growing open source projects in the world, it is the de facto standard for Database DevOps–providing a robust and reliable platform for managing database schema changes across various database types. With 5,000 GitHub Stars and more than 45 million downloads, Liquibase has grown 66% a year, on average, over the last five years. In 2024 alone it was downloaded more than one million times per month.

Using Liquibase, teams can automate and standardize deployments by creating repeatable workflows, reducing manual effort and potential for error. This includes automated policy enforcement to ensure compliance, uphold code standards, and verify code before allowing changes to deploy.

Plus, Liquibase easily integrates with existing CI/CD tools including Jenkins, GitHub Actions, and Azure DevOps, allowing teams to deploy database code the same way they deploy application code. Changes move through existing source code repositories and automation tools before being deployed to the desired databases. Liquibase keeps track of which changes have already been deployed, and only deploys those changes that have yet to go live.

Liquibase also automatically logs data throughout the change management pipeline. With data pipeline analytics, shareable change operation reports, and tracking tables, teams can track DevOps metrics to drive continuous improvement and optimize delivery performance.

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Modern Delivery Demands Database DevOps

Database DevOps is not a new idea but it is more critical than ever. Modern software and data delivery depend on it. Application code has been automated. Infrastructure is delivered as code. The database remains the bottleneck. This is the Velocity Gap.

Database DevOps closes that gap by applying the same discipline, automation, and tooling to database change that engineering teams already apply to the rest of their stack. Every database change is versioned, tested, governed, and delivered through CI/CD in the same way as application code.

This is not just a tooling problem. It is a mindset shift. Teams that embrace it can move fast and stay in control. Teams that do not will fall behind as AI and modern data products raise the bar for delivery.

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Next Action

Liquibase Pro helps organizations eliminate the Velocity Gap by delivering database change faster with the right controls in place.

Get started today.