How do you decide between using Hadoop and GCP?

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Accepted Answer

Hadoop is a distributed open-source framework for storing and processing large datasets, while GCP (Google Cloud Platform) is a cloud computing service that offers various data processing and storage solutions.

Consider the size and complexity of your data: Hadoop is better suited for large-scale batch processing, while GCP offers more flexibility and scalability for various types of workloads.
Evaluate your team's expertise: Hadoop requires specialized skills in managing and maintaining the infrastructure, while GCP provides managed services that require less operational overhead.
Cost considerations: Hadoop can be cost-effective for on-premises deployments, but GCP offers pay-as-you-go pricing and discounts for long-term commitments.
Integration with existing systems: Consider how easily Hadoop or GCP can integrate with your current data sources, tools, and workflows.
Performance requirements: Evaluate the performance capabilities of Hadoop's distributed processing model versus GCP's managed services for real-time or near-real-time processing.

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How do you decide between using Hadoop and GCP?

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