What are S3 storage classes, and how would you choose between them for a data lake?

I-Hub Talent is the best Full Stack AWS with Data Engineering Training Institute in Hyderabad, offering comprehensive training for aspiring data engineers. With a focus on AWS and Data Engineering, our institute provides in-depth knowledge and hands-on experience in managing and processing large-scale data on the cloud. Our expert trainers guide students through a wide array of AWS services like Amazon S3, AWS Glue, Amazon Redshift, EMR, Kinesis, and Lambda, helping them build expertise in building scalable, reliable data pipelines.

At I-Hub Talent, we understand the importance of real-world experience in today’s competitive job market. Our AWS with Data Engineering training covers everything from data storage to real-time analytics, equipping students with the skills to handle complex data challenges. Whether you're looking to master ETL processes, data lakes, or cloud data warehouses, our curriculum ensures you're industry-ready.

Choose I-Hub Talent for the best AWS with Data Engineering training in Hyderabad, where you’ll gain practical exposure, industry-relevant skills, and certifications to advance your career in data engineering and cloud technologies. Join us to learn from the experts and become a skilled professional in the growing field of Full Stack AWS with Data Engineering.

Amazon S3 offers multiple storage classes, each optimized for different use cases based on data access frequency, durability, availability, and cost. For a data lake, choosing the right storage class can significantly impact performance and cost-efficiency.

S3 Storage Classes Overview:

1. S3 Standard

   • For frequently accessed data

   • High durability (99.999999999%) and availability (99.99%)

   • Use for active analytics or frequently queried data

2. S3 Intelligent-Tiering

   • Automatically moves data between frequent and infrequent tiers based on usage

   • Ideal when access patterns are unknown or variable

   • Cost-effective with minimal overhead

3. S3 Standard-IA (Infrequent Access)

   • Lower cost, but charged per retrieval

   • Best for data accessed less frequently but still needed quickly when requested

4. S3 One Zone-IA

   • Similar to Standard-IA but stored in a single AZ (lower cost, less availability)

   • Use for non-critical, infrequently accessed data

5. S3 Glacier

   • Low-cost storage for archive data with retrieval times from minutes to hours

   • Use for data rarely accessed but needed eventually (e.g., historical logs)

6. S3 Glacier Deep Archive

   • Lowest-cost option, retrieval time up to 12 hours

   • For long-term retention and compliance archives

Choosing for a Data Lake:

• Active data (frequently queried): Use S3 Standard or Intelligent-Tiering

• Cold data (rarely accessed but still important): Use Standard-IA or Glacier

• Archived data (compliance, long-term storage): Use Glacier Deep Archive

Intelligent-Tiering is often a great default for data lakes, as it balances cost and performance by auto-adjusting to usage patterns.

Read More

What is the importance of AWS Glue in ETL (Extract, Transform, Load) processes?

How do you automate workflows using AWS Lambda?

Visit I-HUB TALENT Training institute in Hyderabad