In this engaging webinar tailored for Azure SQL...
RED 10: The ‘Git Friendly’ Revolution for CI/CD in Data Warehousing

For years, WhereScape RED has been the engine that powers rapidly built and high performance data warehouses. And while RED 10 has quietly empowered organizations since its launch in 2023, our latest 10.4 release is a game changer. We have dubbed this landmark update our ‘Git Friendly’ release, as it delivers critical enhancements that pave the way for a bold new agile CI/CD process in data warehousing.
A New Chapter in Data Warehousing
Traditional data warehouse development has long been synonymous with slow build times and cumbersome manual processes. In developing RED 10.4, we’ve addressed these challenges head on. By integrating ‘Git Friendly’ features, we’ve enabled development teams to bring version control and collaborative workflows to the very core of data warehouse management.
RED 10.4 isn’t just an incremental update, it’s a paradigm shift. One that breaks down the past position of data warehouses as a decelerator and rebuilds them instead as an accelerator, an enabler, of modern CI/CD processes.
Key Enhancements in RED 10.4
RED 10.4 builds on the robust foundation of previous RED 10 releases and introduces a host of new capabilities, focused on better integration with external development tools:
- Workflow Scripts & Contextual Automation: a brand new workflow script category is now available to you throughout the RED UI. These scripts execute directly from context menus – delivering a JSON file of relevant objects for processing. This functionality simplifies tasks such as automated deployments, metadata export and integration with version control systems.
- ‘Git Friendly’ Integration Improvements: The check-in/check-out feature now triggers scripts that can support Git operations (e.g. ‘push’, ‘pull’ and ‘commit’). New endpoints in the RED metadata service export objects and jobs in a ‘Git Friendly’ JSON format, making it easier than ever to version and manage changes across distributed teams.
- Enhanced 3D Integration: Our new merge settings for source mappings give you precise control over how objects are updated during development from 3D to RED. With options to replace or merge, using either the application or repository rules, teams can now avoid deploying outdated changes and maintain a clean and current master model.
- Expanded Command Line & API Support: RED 10.4 now supports an ‘export all’ option for RedCLI commands and includes new Scheduler API environment variables, along with enhanced Azkaban scheduling and UI improvements. These enhancements facilitate automated testing and job management, all of which are crucial for a robust CI/CD process.

The CI/CD Story: A Broader Perspective
While RED 10.4 marks a significant new step towards ‘Git Friendly’ data warehousing, it’s only part of a wider story.
In our ongoing journey to better support CI/CD practices for data teams, we’re laying fresh foundations for more seamless integration between WhereScape and modern development environments.
Our long term vision is to provide:
- Unified Workflows for Distributed Teams: By empowering teams to branch, commit and merge their changes at an atomic-level of precision – fostering data democratization and enabling a modern Data Mesh approach. While also ensuring that every single modification is traceable and that the master model remains pristine.
- Automated Testing & Deployment: Even with a number of further changes planned to complete our end-to-end CI/CD solution, RED 10.4’s new features make it easier than ever before to integrate with external testing and deployment tools. Imagine the simplicity of pushing a data model from a sandbox environment, to production – all with just a few automated steps!
For more information on how our CI/CD vision is constantly evolving, check out our CI/CD page.
Celebrating a Milestone in RED 10
The many enhancements in RED 10.4 are a culmination of continuous innovation throughout the RED 10 series. By building on the strong, rapid development capabilities that were introduced in earlier versions as well as incorporating these new ‘Git Friendly’ features – we are now redefining what it means to manage data warehouses in a modern DevOps-driven landscape.
From ‘Git Friendly’ to Git Focused: What’s Next?
As we celebrate the release of RED 10.4 with its new features that are exclusive to RED 10.4 (customers on earlier versions are strongly encouraged to migrate), we’re very much excited about the future. Our roadmap looking ahead includes further enhancements in core areas such as automated testing, version control and collaborative integration – ensuring that WhereScape continues to build upon its position at the forefront of CI/CD for data warehousing.
Are you ready to see how these innovations can transform your data development process? Request a demo today and join us on the journey toward a fully integrated, CI/CD-enabled data warehouse.
New in RED 10.5: Streamlined Install, Smarter Upgrades & Enterprise Scale
For many teams, the hardest part of progress isn’t always about what they’re building - instead, it’s staying current, without slowing down. WhereScape RED 10.5 has been developed with that thought squarely in mind. This new release reduces the steps between “we...
Implementing the Medallion Lakehouse on Microsoft Fabric – Fast – with WhereScape
Organizations arriving at Microsoft Fabric often share the same first impression: the platform brings the right ingredients together—OneLake for storage, Data Factory for movement, a lake-centric Fabric Warehouse for SQL performance, and governance that spans the...
Accelerate Microsoft Fabric Adoption with WhereScape Automation
As organizations embrace Microsoft Fabric to streamline their analytics infrastructure, they quickly encounter the complexity inherent in managing multiple integrated components. Microsoft Fabric’s extensive capabilities—from OneLake storage and Data Factory pipelines...
Demystifying Microsoft Fabric Components for Business & Technical Users
Microsoft Fabric is rapidly becoming the go-to solution for enterprises aiming to consolidate their analytics processes under a single comprehensive platform. However, understanding the full scope and function of its components can initially seem daunting to both...
An Introduction to Microsoft Fabric: Unifying Analytics for Enterprises
In today's data-driven world, enterprises face an ever-growing demand to harness data efficiently. The complexity of managing diverse and expansive data sources often presents significant challenges. Microsoft Fabric has emerged as a comprehensive solution designed to...
WhereScape at TDWI Munich: Automate Data Vault on Databricks
WhereScape at TDWI Munich 2025: Automate a Full Data Vault on Databricks in Just 45 Minutes June 24–26, 2025 | MOC Munich, Germany As data complexity grows and business demands accelerate, scalable and governed data architectures are no longer optional—they're...
What Is OLAP? Online Analytical Processing for Fast, Multidimensional Analysis
Streamline your data analysis process with OLAP for better business intelligence. Explore the advantages of Online Analytical Processing (OLAP) now! Do you find it challenging to analyze large volumes of data swiftly? A Forrester study reveals that data teams spend...
Build AI-Ready Data: Visit WhereScape at AI & Big Data Expo
June 4–5, 2025 | Booth 202 | Santa Clara Convention Center As organizations scale their artificial intelligence and analytics capabilities, the demand for timely, accurate, governed, and AI-ready data has become a strategic priority. According to Gartner, through...
Automating Star Schemas in Microsoft Fabric: A Webinar Recap
From Data Discovery to Deployment—All in One Workflow According to Gartner, data professionals dedicate more than half of their time, 56%, to operational tasks, leaving only 22% for strategic work that drives innovation. This imbalance is especially apparent when...
What is a Data Model? How Structured Data Drives AI Success
What is a data model? According to the 2020 State of Data Science report by Anaconda, data scientists spend about 45% of their time on data preparation tasks, including cleaning and loading data. Without well-structured data, even the most advanced AI systems can...