Build vs. buy data pipelines: Costs to consider

Fivetran’s August 2026 discussion of build-versus-buy decisions for data pipelines argues that the main expense of custom integrations is ongoing maintenance rather than initial development, including responding to API and schema changes, outages, security needs, monitoring, and new data-source requests. It cites benchmarks claiming organizations allocate 7.5% of data budgets and 53% of engineering time to pipeline maintenance, while custom or legacy integrations reportedly fail more often than managed alternatives. The piece contrasts this with managed platforms, which use prebuilt connectors, automated maintenance, and configurable transfers to reduce setup time and allow teams to focus on analytics, governance, product work, and AI initiatives. It also emphasizes the opportunity cost of assigning lean engineering teams to infrastructure work, particularly where reliable, current, and complete data is needed for AI projects. Customer examples are presented as evidence of reduced maintenance and labor costs, and the discussion concludes by promoting Fivetran’s more than 750 connectors and Connector SDK as options for centralized, managed data movement, including support for proprietary systems.

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