Webflow Delivers Internal and External Embedded Analytics with Cube Cloud

Webflow is a Website Experience Platform (WXP) that empowers modern marketing teams to visually build, manage, and optimize stunning websites. Webflow’s site builder, CMS, and optimization tools put the power of code in a visual-first front end—where marketing and design can self-serve and engineering can extend with custom code. Webflow has over 300,000 customers in 200+ countries.

Webflow faced a growing need to streamline its data infrastructure. As the company scaled, it became essential to provide consistent data access and interpretation across both engineering and non-engineering teams inside and outside the organization, while maintaining a high level of performance and security. Rocio Delgado, Senior Engineering Manager‬, shares Webflow’s story.

The Challenge of Providing Consistent, Scalable Access for Internal and External Use Cases

Before Cube Cloud, Webflow's engineering team contended with the challenge of providing scalable, centralized data access, not only for the product they were building but also for various internal analytics. Webflow’s site usage dashboard is a customer-facing Analytics dashboard that provides information about bandwidth usage and high-bandwidth pages and assets.

The data that powers this dashboard, needs to be available internally too for billing and offline analysis. With multiple teams relying on data for both use cases, there was a pressing need for an abstraction layer that could offer uniform data interpretation.

Webflow sought a way to provide query scalability while simplifying data access. The primary goal was to develop a universal semantic layer that could define business logic consistently across the organization. This solution had to be scalable, secure, easy to implement, and cost-effective, while also supporting Webflow’s existing API infrastructure.

Why Webflow Chose Cube Cloud

Webflow chose Cube Cloud for performance, flexibility, ease of use, and scalability. The decision to implement Cube Cloud was driven by its ability to power real-time data dashboards and its compatibility with Webflow’s tech stack. Cube’s performance features, such as query caching, provided the speed necessary for responsive analytics.

Webflow successfully integrated Cube Cloud into its infrastructure, pairing it with ClickHouse for high-performance querying. Webflow achieved a p95 of 220 milliseconds using Cube Cloud’s advanced caching capabilities with ClickHouse. Cube Cloud helped the team to ensure streamlined version control and easier collaboration between teams.

Additionally, Cube's flexibility with multiple data sources and its ease of use—particularly in defining complex metrics and access through REST and GraphQL APIs—made it the perfect fit for Webflow’s needs. Cube’s Data APIs allowed Webflow to easily integrate with various front-end‬ applications and third-party tools. This flexibility has made it easier to build and maintain data-driven applications.‬

“We integrated Cube Cloud smoothly with ClickHouse, leveraging both for fast query‬ execution while maintaining the abstraction needed for different teams to access data‬ without diving into database-specific complexities.‬”

— Rocio Delgado, Senior Engineering Manager, Webflow

Webflow Delivers Unified Data with Cube Cloud

Since implementing Cube Cloud, Webflow has seen a marked improvement in data accessibility and governance. Real-time analytics development timelines have been slashed, thanks to Cube Cloud’s architecture and native APIs, which eliminated the need for custom-built API layers.

Enhanced speed and scalability have enabled Webflow’s teams to focus on innovation without being bogged down by data complexities. Cube Cloud’s universal semantic layer has not only improved Webflow's internal data processes but also empowered the organization to deliver more consistent and efficient data-driven experiences for its users.

Cube Cloud’s universal semantic layer transformed how Webflow accesses and uses data. By centralizing business logic, it eliminated inconsistencies across teams and allowed for rapid deployment of new data models. The REST API integrations facilitated smooth data flows into Webflow’s front-end applications, simplifying the build and maintenance of data-driven features.