AWS Partner Network (APN) Blog
Tag: Neo4j
Say Hello to 182 AWS MSP, Service Ready, Service Delivery, and Competency Partners Added or Renewed in June
We are excited to highlight 182 AWS Partners that received new or renewed designations in May for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.
When to Use a Graph Database Like Neo4j on AWS
Graph databases are useful for solving problems related to connected data, and represent data as nodes and enable organizations to uncover relationships between data that’s not possible with other approaches. Experts from AWS and Neo4j explore four types of databases and the most common applications for each: relational, document, in-memory, and graph. We’ll cover how different industries use graph databases and how they work as part of an AWS architecture.
Say Hello to 143 AWS Competency, Service Delivery, Service Ready, and MSP Partners Added or Renewed in March
We are excited to highlight 143 AWS Partners that received new or renewed designations in March for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.
Create Dynamic Serverless Applications with Neo4j Graph Database and AWS Lambda
The AWS Cloud Development Kit (AWS CDK) is a framework that provides an automated and repeatable way of handling cloud infrastructure. Learn how to use the AWS CDK to build an AWS Lambda function in Java that connects to Neo4j. The framework described here can be used to build dynamic serverless applications where the frontend scales based on system demand. This makes it possible to easily get value from your connected graph data in front end applications.
Graph Feature Engineering with Neo4j and Amazon SageMaker
Featurization is one of the most difficult problems in machine learning. Learn how graph features engineered in Neo4j can be used in a supervised learning model trained with Amazon SageMaker. These novel graph features can improve model performance beyond what’s possible with more traditional approaches. Together, these components offer a graph platform that can be used to understand graph data and operationalize graph use cases.
Say Hello to 112 New AWS Competency, Service Delivery, Service Ready, and MSP Partners Added in September
We are excited to highlight 112 AWS Partners that received new designations in September for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.