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Description
Amazon AppFlow is a comprehensive integration service that allows for the secure transfer of data between various Software-as-a-Service (SaaS) applications, such as Salesforce, Marketo, Slack, and ServiceNow, along with AWS services like Amazon S3 and Amazon Redshift, all with just a few clicks. It facilitates the execution of data flows at virtually any scale, allowing users to determine the frequency of these operations—whether on a set schedule, triggered by a business event, or initiated on demand. AppFlow also offers data transformation features like filtering and validation, enabling users to create rich, ready-to-use datasets as part of the flow without the need for extra steps. Furthermore, it ensures that data is automatically encrypted during transit, and it provides options for users to prevent data from traversing the public internet when using SaaS applications integrated with AWS PrivateLink, thereby minimizing the risk of security vulnerabilities. By default, any data transfers involving SaaS integrations that utilize AWS PrivateLink are protected from exposure to the public internet, enhancing overall data security. This level of integration not only simplifies the process but also boosts confidence in managing sensitive information securely.
Description
Amazon SageMaker is a comprehensive machine learning platform that integrates powerful tools for model building, training, and deployment in one cohesive environment. It combines data processing, AI model development, and collaboration features, allowing teams to streamline the development of custom AI applications. With SageMaker, users can easily access data stored across Amazon S3 data lakes and Amazon Redshift data warehouses, facilitating faster insights and AI model development. It also supports generative AI use cases, enabling users to develop and scale applications with cutting-edge AI technologies. The platform’s governance and security features ensure that data and models are handled with precision and compliance throughout the entire ML lifecycle. Furthermore, SageMaker provides a unified development studio for real-time collaboration, speeding up data discovery and model deployment.
API Access
Has API
API Access
Has API
Integrations
Amazon Redshift
Amazon Transcribe
Splunk User Behavior Analytics
Acryl Data
Amazon FSx for Lustre
Amazon Linux 2
Amazon Nova Forge
Amazon SageMaker Debugger
Amazon SageMaker JumpStart
Comet
Integrations
Amazon Redshift
Amazon Transcribe
Splunk User Behavior Analytics
Acryl Data
Amazon FSx for Lustre
Amazon Linux 2
Amazon Nova Forge
Amazon SageMaker Debugger
Amazon SageMaker JumpStart
Comet
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/appflow/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/
Product Features
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Product Features
Data Labeling
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization