Global Communication Platform Achieves 110% Faster Analytics with Databricks Lakehouse

Grammarly, a global leader in AI-powered communication assistance, serves 30 million people and 50,000 teams with real-time writing suggestions across spelling, grammar, clarity, and tone. As a technology and software company processing approximately 5 billion user events daily, Grammarly faced critical limitations with its legacy, homegrown analytics platform. The legacy system relied on a proprietary SQL-like language that hindered onboarding, lacked support for external data integration, and could not connect to modern visualization tools like Tableau. Additionally, large Amazon EMR clusters running continuously drove up infrastructure costs, while fragmented data warehouses created access control challenges and organizational data silos that impeded cross-functional decision-making.

To address these constraints while maintaining industry-leading security standards, Grammarly migrated to the Databricks Data Intelligence Platform, implementing a lakehouse architecture with Delta Lake at its core. The solution consolidated all analytical data into a unified repository, enabling analysts to use standard Databricks SQL for querying both internal product data and external third-party advertising data. Unity Catalog provided fine-grained, role-based access controls and real-time data lineage monitoring—critical for Grammarly's enterprise-grade security requirements and compliance objectives. This centralized approach eliminated data silos, created a single source of truth across the organization, and enabled seamless integration with Tableau for executive dashboards and stakeholder reporting.

The migration delivered measurable improvements in speed, cost, and collaboration. Grammarly now executes queries 110% faster at 10% of the ingestion cost compared to its previous data warehouse, while reducing data availability time from 4 hours to under 15 minutes for its 5 billion daily events. Marketing teams rapidly analyze user lifetime value against customer acquisition costs across advertising channels, while product teams receive near-real-time feedback on feature adoption and user engagement patterns. The unified platform removed technical barriers, enabling analysts and data engineers to work collaboratively under one infrastructure rather than maintaining separate tools. By consolidating data warehouses and eliminating expensive 24/7 EMR clusters, Grammarly reduced operational overhead while gaining the flexibility to scale alongside business growth—fundamentally transforming how the company makes data-driven decisions to improve communication for millions of users worldwide.