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Home/Questions/Cloud/Tools/What are the pros and cons of using a data lake on AWS, GCP, or Azure?

What are the pros and cons of using a data lake on AWS, GCP, or Azure?

Cloud/Toolshard0.4 min readPremium

**AWS**: Mature ecosystem (S3, Glue, Athena, EMR). Strong for hybrid (DataSync, Snowball). Service sprawl—many options, steeper learning. **GCP**: Strong BigQuery (serverless SQL); Dataflow (Beam); good integration. Smaller market share; fewer third-party integrations....

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
179
questions in Cloud/Tools
Difficulty Split
104E|27M|48H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
BCG
Key Concepts Tested
bigquerysql

Why This Question Matters

This hard-level Cloud/Tools question appears frequently in data engineering interviews at companies like BCG. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (bigquery, sql) will help you answer variations of this question confidently.

How to Approach This

This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.

Expert Answer
78 words

AWS: Mature ecosystem (S3, Glue, Athena, EMR). Strong for hybrid (DataSync, Snowball). Service sprawl—many options, steeper learning. GCP: Strong BigQuery (serverless SQL); Dataflow (Beam); good integration. Smaller market share; fewer third-party integrations. Azure: ADLS Gen2 (hierarchical namespace); Synapse combines lake + warehouse. Strong enterprise presence; complexity in multi-service setup. Decision factors: Existing cloud commitment, team skills, compliance (region availability), cost (run TCO analysis). Best practice: Choose by organizational context; don't multi-cloud without clear reason. All support medallion architecture.

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According to DataEngPrep.tech, this is one of the most frequently asked Cloud/Tools interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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