Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon Macie is an entirely managed service focused on data security and privacy that leverages machine learning and pattern recognition to locate and safeguard sensitive information within AWS.
As organizations grapple with the increasing amounts of data they generate, the task of identifying and securing sensitive information can become more complex, costly, and labor-intensive. By automating the process of discovering sensitive data at scale, Amazon Macie helps reduce the financial burden associated with data protection. It generates an inventory of Amazon S3 buckets, highlighting unencrypted buckets, those that are publicly accessible, and those shared with AWS accounts outside your designated AWS Organizations. Additionally, Macie utilizes machine learning and pattern matching methods on the selected buckets to pinpoint and notify you about sensitive data, including personally identifiable information (PII), ensuring that your organization remains compliant and secure. Furthermore, by streamlining this process, Macie enables businesses to focus more on their core operations while maintaining robust data security practices.
Description
Amazon S3 Vectors is the pioneering cloud object storage solution that inherently accommodates the storage and querying of vector embeddings at a large scale, providing a specialized and cost-efficient storage option for applications such as semantic search, AI-driven agents, retrieval-augmented generation, and similarity searches. It features a novel “vector bucket” category in S3, enabling users to classify vectors into “vector indexes,” store high-dimensional embeddings that represent various forms of unstructured data such as text, images, and audio, and perform similarity queries through exclusive APIs, all without the need for infrastructure provisioning. In addition, each vector can include metadata, such as tags, timestamps, and categories, facilitating attribute-based filtered queries. Notably, S3 Vectors boasts impressive scalability; it is now widely accessible and can accommodate up to 2 billion vectors per index and as many as 10,000 vector indexes within a single bucket, while ensuring elastic and durable storage with the option of server-side encryption, either through SSE-S3 or optionally using KMS. This innovative approach not only simplifies managing large datasets but also enhances the efficiency and effectiveness of data retrieval processes for developers and businesses alike.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
AWS App Mesh
AWS Security Hub
Amazon Aurora
Amazon Bedrock
Amazon CloudWatch
Amazon Detective
Amazon OpenSearch Service
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Integrations
Amazon S3
AWS App Mesh
AWS Security Hub
Amazon Aurora
Amazon Bedrock
Amazon CloudWatch
Amazon Detective
Amazon OpenSearch Service
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/macie/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/s3/features/vectors/
Product Features
Cybersecurity
AI / Machine Learning
Behavioral Analytics
Endpoint Management
IOC Verification
Incident Management
Tokenization
Vulnerability Scanning
Whitelisting / Blacklisting