Amazon S3
Business Profile
Core Value Proposition
Amazon S3 provides scalable, durable cloud object storage with high availability, security, and performance for data lakes, cloud-native apps, backups, archival, AI/ML, and analytics.
Target Customer
Developers, IT teams, data engineers, data scientists, and business units needing scalable object storage for data lakes, backups, archival, AI/ML workflows, and analytics.
Key Differentiator
11 nines (99.999999999%) data durability and 99.99% availability by default, no provisioning required, multiple storage classes with lifecycle management, strong security and access controls, and seamless integration with AWS services.
Implementation Timeline
Not specified in the provided content
Pain Points
- 1Need to store virtually any amount of data with no upfront provisioning
- 2Requirement for extremely high durability and availability with security controls
- 3Desire to optimize costs via storage classes and automated data lifecycle management
Key Features
- 1Storage classes and lifecycle management
- 2S3 Versioning to retain multiple object versions
- 3Bucket policies, IAM policies, S3 Access Points, and ACLs for access control
- 4Data encryption by default and auditing capabilities
- 5S3 Glacier and Glacier Deep Archive for archival storage
- 6Data lake capability with cross-service integration
Target Customer Industries
Decision Makers
- 1Senior Director of Media and Event Technology, NASCAR
- 2Chief Technology Officer, Dropsuite
- 3Director of Engineering, Pomelo
- 4Health Cloud, Learning Factory, and Core Services engineer, GE Healthcare Digital
Client Results
- 1Ancestry restored terabytes of images in hours using Glacier storage classes
- 2BBC migrated a 100-year archive to S3 Glacier Instant Retrieval
- 3Dropsuite cites 400% growth in users and data with optimized IT budgets
- 4NASCAR modernized its technology stack with S3-based storage enabling more time for developing workflows
- 5Salesforce case study demonstrates using a data lake built on S3 to discover, access, and analyze data across the organization
- 6Pomelo case study describes a data repository that expands dynamically with minimal maintenance and integrates with AWS services while meeting compliance
- 7GE Healthcare Digital case study highlights durability and reliability for storing critical data
Competitive Advantages
- 1Industry-leading scalability and capacity (exabytes, 350 trillion objects)
- 2Highest durability (11 nines) and strong availability
- 3Flexible storage classes and automated lifecycle management
- 4Zero provisioning; pay-as-you-go pricing
- 5Integrated with AWS ecosystem for data lakes and analytics
- 6Secure by default with comprehensive access controls
Key Benefits
Case Studies & Success Stories
Salesforce case study
Using a data lake built on Amazon S3 to discover, access, and analyze all data across Salesforce's organization in a secure and governed way.
Ancestry case study
Uses Amazon S3 Glacier storage classes to restore terabytes of images in hours rather than days.
BBC case study
Safely migrated its 100-year archive to Amazon S3 Glacier Instant Retrieval.
Dropsuite case study
Customer growth and IT budget optimization enabled by scalable, integrated S3 storage.
Pomelo case study
A data repository that expands dynamically with minimal maintenance and integrates with other AWS services while meeting compliance.
GE Healthcare Digital case study
S3 storage provides durability and reliability for storing critical data across Health Cloud, Learning Factory, and Core Services.
Additional Product Information
Product Description
Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance for data lakes, cloud-native applications, and mobile apps.
Target Market
Organizations needing scalable object storage for data lakes, backups, archival, AI/ML, and analytics across various industries.
Unique Value Proposition
Unmatched durability and availability, broad storage class options, cost optimization, and seamless AWS integration enabling data lake and AI/ML workflows.
Technical Requirements
To store data, you create a bucket in an AWS Region and upload objects. Objects have keys; access is controlled with bucket policies, IAM policies, S3 Access Points, and ACLs. Features include S3 Versioning for multiple object versions and private default access. Encryption and auditing capabilities are available.
Pricing Model
Pay-as-you-go pricing with a free tier option; no upfront provisioning; cost optimization via storage classes and lifecycle policies.
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