Amazon Authenticator
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KNIME for AWS Users
Unlock the full potential of your AWS infrastructure with KNIME. From basic storage and file management to scalable cloud databases and advanced MLaaS offerings, the KNIME AWS extensions make it very easy to incorporate the power of AWS by just adding a few nodes. Keep in mind that executing KNIME workflows connected to AWS may incur AWS costs.
KNIME AWS Integrations User Guide
This guide illustrates how to connect to AWS and how to use the AWS extensions.
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Getting Started with AWS Workflows
Utilizing AWS product connections within KNIME will always start with user authentication. Once you have authenticated, you can use that output to power the AWS connectors.
Connecting to Data Stored in AWS
KNIME supports importing different types of data from multiple different AWS products. Depending on the AWS product, you can incorporate KNIME frameworks for additional processing.
File Storage with KNIME File Handling
With the KNIME File Handling Framework and Amazon S3 Connector, you can incorporate files stored in Amazon S3 into your workflows.
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This workflow demonstrates how to read data files (Text, Excel, KNIME Table and CSV) from the Amazon S3.
knime > Beginners Space > 01_Read > 04_Read_Data_from_Amazon_S3
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Relational Databases with KNIME’s Database Framework
With KNIME’s Database Connectivity Framework, you can incorporate database tables stored in AWS into your KNIME Workflows. This includes AWS database services like Redshift and Athena, as well as databases provisioned via Amazon RDS.
No-SQL/Key-Value Databases (DynamoDB)
Adding DynamoDB to your workflows allows you to incorporate the power of a NoSQL database into your KNIME Workflows and Data Applications.
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Extension
KNIME Amazon DynamoDB Nodes
This feature contains the Amazon DynamoDB nodes.
KNIME AG, Zurich, Switzerland
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Leveraging Amazon EMR with KNIME’s Apache Spark Framework
With the KNIME Extension for Apache Spark, KNIME user’s can leverage data from spark clusters created using Amazon EMR into their workflows.
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Extension
KNIME Extension for Apache Spark
KNIME nodes for assembling, executing and managing Apache Spark applications. Supports Spark versions 2.4 and 3.
KNIME AG, Zurich, Switzerland
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Connecting to Amazon Machine Learning Products
KNIME offers native connectors for a few Amazon MLaaS offerings, including Amazon Comprehend, Amazon Personalize, and Amazon Translate. See below the full node extension.
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Extension
KNIME Amazon Machine Learning Integration
This feature contains nodes for interacting with AWS (Amazon Web Services) AI/ML-Services like AWS Comprehend and AWS Translate.
KNIME AG, Zurich, Switzerland
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Workflow
Amazon Personalize Movie Recommendation Example
Generates personalized movie recommendations using Amazon Personalize web services.
knime > Examples > 40_Partners > 02_Amazon > 03_Amazon_Personalize_Movie_Recommendation_Example
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Workflow
Travel Risk Map for Corporate Safety using AWS Comprehend and Translate
Generates Travel Risk Map for Corporate Safety using AWS Comprehend and Translate.
knime > Examples > 40_Partners > 02_Amazon > 02_Amazon_Comprehend_Translate_Travel_Risk_Map
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Using Boto3 in KNIME Python Nodes
Learn how to connect to AWS services using Boto3 in KNIME Python Nodes
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Provides an overview of KNIME’s Python integration and how Python scripts can be used in workflows.
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KNIME on AWS Marketplace
KNIME provides AWS Marketplace offerings for customer-managed instances of KNIME Business Hub and KNIME Analytics Platform. If you are interested in deployment of KNIME Business Hub via the AWS Marketplace, refer to the following links and documentation. If you need assistance on evaluation of this deployment, please contact KNIME Customer Care using the link below.