What are the core storage services in AWS and how are they used in data pipelines?

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AWS offers several core storage services essential to building robust data pipelines:

1. Amazon S3 (Simple Storage Service): A scalable object storage service used for storing raw, processed, and curated data. It’s often the starting point of data pipelines, where data is ingested from various sources and stored as files (e.g., CSV, JSON, Parquet). S3 integrates well with services like AWS Glue, Athena, EMR, and Redshift for further processing and analytics.

2. Amazon EBS (Elastic Block Store): Provides block-level storage for EC2 instances, typically used for high-performance applications like databases or intermediate storage during data transformation in custom ETL scripts.

3. Amazon EFS (Elastic File System): A scalable file storage for use with EC2, ideal for applications that require shared access and parallel processing, such as data science workloads or batch processing stages in a pipeline.

4. Amazon FSx: Managed file systems (e.g., FSx for Lustre) used for high-performance computing and analytics workloads requiring fast, parallel access to data.

5. Amazon Glacier (S3 Glacier): A long-term archival storage service, useful for storing historical or infrequently accessed pipeline data at low cost.

In a typical data pipeline, S3 acts as the main data lake, storing all stages of data. ETL tools (like Glue) read/write from S3, EBS/EFS support processing, and Glacier stores archived results. Together, these services ensure efficient, scalable, and cost-effective data pipeline operations.

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