Naveenkvisualpath1142
Uploaded on Dec 27, 2025
Category
Education
Boost your data engineering career with Visualpath’s industry-focused cloud program. Join the Data Engineering course in Hyderabad to master ETL pipelines, data processing, and analytics through hands-on projects and guided labs. Enroll in AWS Data Engineering training to gain expert mentorship, job-ready skills, and support for global certification. Call +91-7032290546 today. Visit: https://www.visualpath.in/online-aws-data-engineering-course.html WhatsApp: https://wa.me/c/917032290546 Blog link: https://visualpathblogs.com/category/aws-data-engineering-with-data-analytics/
Category
Education
Data Engineering course in Hyderabad - AWS Data Engineering
AWS DATA WAREHOUSE VS
DATA LAKE
• Introduction to AWS analytics storage
• Two different approaches for data storage
• Used for analytics, reporting, and insights
• Important concept for data engineers
• Common interview and architecture topic
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WHAT IS AN AWS DATA
WAREHOUSE?
• Stores structured and processed data
• Optimized for fast analytical queries
• Uses schema-on-write approach
• Ideal for BI and reporting
• Example service: Amazon Redshift
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WHAT IS AN AWS DATA LAKE?
• Stores raw data in original format
• Supports all data types
• Uses schema-on-read approach
• Used for analytics and ML
• Example service: Amazon S3
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DATA STRUCTURE
DIFFERENCES
• Warehouse stores cleaned data
• Lake stores raw and unprocessed data
• Warehouse requires predefined schema
• Lake allows flexible analysis
• Lake supports more data variety
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PERFORMANCE AND QUERY
USAGE
• Warehouse optimized for SQL queries
• Faster performance for reporting
• Lake depends on processing engine
• Athena and EMR used for lake queries
• Warehouse preferred for dashboards
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COST AND SCALABILITY
• Warehouse has higher compute cost
• Cost increases with query load
• Lake offers low-cost storage
• Pay only when processing data
• Lake scales easily for big data
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AWS SERVICES COMPARISON
• Warehouse: Amazon Redshift
• Lake: Amazon S3
• Glue used for ETL processes
• Athena used for querying lakes
• Both integrate with AWS tools
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WHEN TO USE WHICH?
• Use Warehouse for BI reporting
• Use Lake for raw and large data
• Many companies use both
• Lake feeds data to warehouse
• Choosing right improves performance
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CONTACT
AWS Data Engineering
Address:- Flat no: 205, 2nd Floor, Nilgiri Block, Aditya
Enclave, Ameerpet, Hyderabad-1
• Ph. No: +91-7032290546
• Visit: www.visualpath.in
• E-Mail: [email protected]
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THANK YOU
Visit: www.visualpath.in
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