wide variety of sources it supports for data integration.

makes the data transfer easy, as compared to other platforms

What I like most about Fivetran is how it has simplified our overall data integration workflow. We initially chose Fivetran because we wanted to avoid building and maintaining custom ingestion pipelines for every data source. As our requirements grew, we started using Fivetran across multiple sources, and it has allowed us to manage these integrations through a much more centralized and automated approach. From a UI/UX perspective, the platform is clean and straightforward to work with. Setting up connectors, selecting schemas and tables, checking sync status, and monitoring the overall health of pipelines is relatively simple. It gives our data engineering team good visibility without requiring us to build separate monitoring solutions. Integrations are definitely one of the biggest strengths for us. We are working with multiple sources such as ShipHero, Shopify, Gorgias, and other systems, and having pre-built connectors has saved us a significant amount of development and maintenance effort. Instead of developing and maintaining individual API ingestion workflows, we can rely on Fivetran to handle the extraction and synchronization. In terms of performance and reliability, the automated incremental synchronization and scheduling have been very useful. The alerts around pipeline failures, sync issues, and rescheduling also help us identify problems quickly without having to constantly monitor every pipeline manually. Another major positive has been the support and onboarding experience. We have faced some fairly complex connector and data-related issues, particularly with ShipHero, including schema changes, historical synchronization, permissions, missing fields, and data reconciliation. What impressed me was that the support team didn't simply provide generic troubleshooting steps. They took the time to understand our business requirements, investigate the issues, and coordinate with Engineering and Product where necessary. Some of the issues we raised resulted in connector improvements and fixes, which has been very valuable for us. From a pricing and ROI perspective, Fivetran has helped reduce the engineering effort required to build and maintain integrations. The fact that historical syncs are not charged has also been particularly useful when initially loading and backfilling data. For us, the value comes not only from the data movement itself, but also from the engineering time saved on maintaining custom integrations. For AI and intelligence, this isn't the primary reason we currently use Fivetran, but I see the broader potential of having reliable, centralized, and continuously synchronized data as an important foundation for downstream analytics and AI-driven data products. Overall, Fivetran has helped us reduce custom engineering work, improve pipeline visibility, and make our data integration process much easier to manage. Combined with the responsive support team and their willingness to work through complex requirements with us, it has been a valuable part of our data engineering workflow.