4 data architecture challenges modern data lakes solve

Modern data lakes offer a solution to the common challenges faced by technical teams in managing data platforms, such as complexity, vendor lock-in, rising costs, and limited data retention. By decoupling storage from compute and embracing open table formats, data lakes provide a more flexible, cost-efficient, and simplified architecture. The Fivetran Managed Data Lake Service further enhances these benefits by automating data ingestion, absorbing compute-heavy pipeline costs, and eliminating the burden of maintaining complex infrastructures. This service addresses compliance issues by centralizing and deduplicating data storage, supports diverse compute engines to avoid vendor lock-in, reduces costs by eliminating redundant data ingestion, and offers unlimited, cost-effective storage for historical data. By integrating the scalability of data lakes with the usability of data warehouses, Fivetran's service enables data teams to manage fewer pipelines, choose optimal query engines, and maintain lower and more predictable costs, all while preserving historical data without performance trade-offs.

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