The Fivetran–dbt merger tests the future of open source in a SaaS-dominated world. Can dbt Core stay community-driven as corporate incentives reshape the modern data stack? Here’s what’s at stake—and what comes next.
Uncover how Fivetran’s pricing shifts and the dbt merger reveal the hidden costs of modern data integration. Learn how to predict changes, protect budgets, and avoid costly surprises.
The modern data stack has failed. The Fivetran–dbt merger highlights tool sprawl, rising costs, and integration complexity, forcing data leaders to rethink their infrastructure strategy. Choose wisely.
When data quality drops, revenue follows. Automated ETL fixes that by eliminating errors, enforcing standards, and ensuring consistency across systems to deliver trustworthy analytics and business insights.
Poor data management can cost organizations 15–20% of revenue. Reusable, scalable data products help—but only if they’re consistent and reliable. A Common Data Model (CDM) standardizes and structures data, ensuring accuracy, scalability, and long-term value.
The Fivetran–dbt merger is creating ripples across the data world. Customers face rising costs and vendor lock-in, while platform giants gain leverage. Learn what the market really thinks and how to stay flexible amid the change.
In the News: In this episode of theCUBE + NYSE Wired Mixture of Experts series, Nexla Co-Founder & CEO Saket Saurabh joins host John Furrier to discuss the future of AI and data. From innovations in context engineering to the rise of AI factories, Saket shares insights on the challenges and opportunities shaping enterprise AI today.
Fivetran and Nexla are leading data integration platforms, but they take different approaches. Learn how they compare on features, deployment, and governance to find the right fit for your data strategy.
In the News: Nexla is featured on DBTA Big Data Quarterly’s 2025 “Big Data 75,” recognized among the innovators driving progress in data collection, storage, and analytics.
Dive into Apache Iceberg’s benefits. Reliable pipelines need strong operations, from catalog options to lakehouses. Learn about time travel, schema evolution, and best practices for scalable maintenance with Nexla.
Most data teams waste time fixing brittle pipelines instead of driving insights. See how AI-powered transformation and Nexla’s Common Data Model cut manual work and ensure scalable pipelines.
In the News: Forbes recognizes how Nexla defines and enables automated data mapping—matching data fields across systems to reduce errors and fragmentation. By applying AI and machine learning to integration, Nexla helps make financial data flows more accurate and resilient.
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