Adaptive Data Pipeline Framework for Unified Ingestion Patterns for Diverse Data Ecosystems

Author(s)	Gayatri Tavva
Country	India
Abstract	Earlier, the emergence of the need for rapid diversification of data sources and the real-time analytics requirements has uplifted the role that adaptive data ingestion frameworks play in the modern digital ecosystem. Adaptive models are different from static ingestion pipelines; they enable accommodating schema variability, streaming fluctuations, or multimodal integration at scale. The architectural principles, operational challenges, and technological advancements that provide a common underlying pattern of unified ingestion across structured, semi-structured, and unstructured data sources are reviewed. Specific emphasis is placed on modular frameworks, machine learning enhanced control mechanisms, and feedback-driven pipeline optimization. The review concludes by outlining current gaps and future research directions to tackle automation, semantic routing, and edge native intelligence in ingestion systems.
Keywords	Adaptive Pipelines, Data Ingestion, Elastic Data Frameworks
Field	Engineering
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-06-28
DOI	https://doi.org/10.71097/IJSAT.v16.i2.6106
Short DOI	https://doi.org/g9r8gh

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International Journal on Science and Technology