Snowflake + AWS Resources
Snowflake, the data warehouse built for the cloud, on AWS is an industry-leading platform for both advanced data analytics and machine learning/AI. Below are some resources you can use to learn about how Snowflake + AWS are #bettertogether.
Snowflake is integrated with a number of AWS native services, and is also a compelling data platform for machine learning/AI applications, providing performant, low-cost, and controlled access to data.
Snowflake fits right into AWS’s data ecosystem, including Data Lakes on AWS, as well as a a number of services you can use to ingest data into Snowflake, including Amazon Kinesis, AWS PrivateLink, AWS Glue, Amazon EMR, or Amazon Managed Kafka Service (MSK).
Snowflake can also leverage Amazon SageMaker, Forecast or Personalize for machine learning/AI and Amazon Quicksight for dashboards.
Together, AWS and Snowflake provide a compelling solution for data, analytics and machine learning that is #bettertogether.
Snowflake + AWS Data Lakes
Auto Ingest Snowpipe is Now Available
HowTo: Configuration Steps for Snowpipe Auto-Ingest with Amazon S3 Stages
Use credential-less Stages to Secure Your Cloud Storage Without Sharing Secrets
Analyze Streaming Data from Amazon Managed Streaming for Apache Kafka Using Snowflake
Snowflake + Amazon Sagemaker
Snowflake + Sagemaker White Paper
Quickstart Guide for Snowflake + Sagemaker (Part One)
Quickstart Guide for Snowflake + Sagemaker (Part Two)
Quickstart Guide for Snowflake + Sagemaker (Part Three)
Quickstart Guide for Snowflake + Sagemaker (Part Four)
Preconfigured Amazon Sagemaker Instance with Snowflake Connector
Snowflake + AWS Machine Learning
Integrating Snowflake Data with Amazon Forecast and Amazon Personalize
Snowflake + AWS Glue
Using AWS Glue to call Stored Procedures in Snowflake
Setting Up Minimum Privileges Required for Read/Write from AWS Glue to Snowflake
Snowflake + AWS Lambda
Snowflake External Functions Now Available in Public Preview