Redgate Software this month detailed a release of Redgate Flyway Enterprise, the company’s database change control solution. With a promise to future-proof software delivery from the risks of rapid AI-driven development, just how much change control do databases need and just how far-reaching are the company’s tools in this space?
Key reasons any enterprise software team might need to perform database change control procedures include the clear (and perhaps obvious) danger posed by the risks stemming from AI-generated code. Change control could also be required to enforce changing (inevitably continuous) compliance and provide auditable change tracking; to validate schema modifications (to support new features, improve performance, or fix flaws) prior to deployment; or perhaps to (more straightforwardly) to maintain stack-wide visibility across complex database infrastructure.
Or, database change control might just happen because teams realise they need to reduce data service deployment lead times and reduce operational support requests.
Flyway Enterprise MCP Server
New from Redgate is Flyway Enterprise MCP Server, a service for teams that need to bring a governed, agentic approach to managing database change. It extends to advanced Databricks capabilities and capabilities for Snowflake, with operational and security dashboard views also on the roadmap.
“AI is the biggest opportunity in a generation to accelerate software creation, and enterprise leaders want to seize it with confidence,” said Jakub Lamik, CEO of Redgate. “The organisations that win will be the ones that pair AI speed with strong foundations. Redgate makes the database ready for that world.”
Lamik suggests that the investments in Redgate Flyway Enterprise mean IT leaders can embrace AI-generated code and agentic workflows, but stay secure in terms of governance and compliance for the database.
Flyway Enterprise MCP Server works to ensure “every AI-driven change is captured, validated and auditable” so compliance is built into the workflow.
The company says it is also deepening visibility and connecting change control directly to estate-wide insight by integrating its flagship products, Redgate Flyway Enterprise and Redgate Monitor, a database observability solution.
CEO Lamik talks to Techzine
Speaking exclusively to Techzine, Redgate CEO Lamik said that AI is the “biggest opportunity in a generation” to accelerate the software delivery lifecycle, and development teams want to seize on it with control and confidence.
“For developers, this means the ability to make changes fast, knowing safeguards will catch problems before they become incidents. With Flyway Enterprise’s MCP server, AI-generated database changes are automatically captured, validated and tracked. Combining this with Flyway’s guardrails gives developers an AI workflow for database changes that is tested, repeatable and reliable, without compromising on speed,” said Lamik.
“The advanced Databricks capabilities in this release, together with upcoming Snowflake ones, extend that same discipline beyond transactional databases and into the analytics estate, where AI initiatives increasingly live. And with the dashboard capabilities we’re building next, teams will get clear, real time visibility into what’s changed across their entire estate,” he added.
“Without this visibility and governance, risk from AI-accelerated change will continue to escalate, and Gartner projects that by 2027, 40% of enterprises will decommission autonomous AI agents due to critical governance gaps exposed after costly production incidents occur. While generic AI tools treat the database like any ordinary deployment target, Redgate is developing AI that understands the database estate, anticipates failures, and enforces workflows before changes are made,” stated the company.
New operational and security dashboard views will be delivered as part of Redgate’s vision for database change control in an agentic era, providing database estate health for teams as they deploy AI into their operations.
Snowflake & Databricks capabilities expanded
For Snowflake: Redgate’s is extending its governed approach to schema change into the analytics estate as AI initiatives increasingly rely on it.
For Databricks capabilities (and the upcoming Snowflake ones) the company is extending discipline beyond transactional databases and into the analytics estate, where AI initiatives increasingly live. This means that data pipelines feeding models and dashboards are governed with the same rigour as production systems.
Redgate Flyway Enterprise aims to be a version-controlled, automated, and deterministic change control system for the database layer. The release aims to target the root causes of deployment failure: manual steps, environment inconsistency, and insufficient pre-deployment validation. This automation framework has driven a 58% to 98% reduction in change lead times and slashed operational support requests by 90%, for customers like Verizon Connect.
What should developers think next?
As software developers are increasingly classed as data-developers, data-DevOps gurus and even data scientists with respect to the amount of AI-assisted coding that is now happening, knowing where autonomous agents and copilots might affect rapid database changes is important if teams don’t want to shatter production environments.
Knowing that autonomous schema modifications won’t bypass compliance and that live production code environments will stay up and operational (if we accept what Redgate is saying) is, of course, fundamental to avoiding emergency rollback sessions and achieving higher deployment frequency.
AI code is one thing, AI code that impacts the core data substrate is another and developers will want to know they’re standing on firm foundations in terms of the information pipe that they feed modern apps with.