HAQM Neptune Generally Available

HAQM Neptune is now Generally Available in US East (N. Virginia), US East (Ohio), US West (Oregon), and Europe (Ireland). HAQM Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. At the core of Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with millisecond latencies. Neptune supports two popular graph models, Property Graph and RDF, through Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune can be used to power everything from recommendation engines and knowledge graphs to drug discovery and network security. Neptune is fully-managed with automatic minor version upgrades, backups, encryption, and fail-over. I wrote about Neptune in detail for AWS re:Invent last year and customers have been using the preview and providing great feedback that the team has used to prepare the service for GA.

Now that HAQM Neptune is generally available there are a few changes from the preview:

• A large number of performance enhancements and updates
• AWS CloudFormation support
• AWS Command Line Interface (AWS CLI)/SDK support
• Updated to Apache TinkerPop 3.3.2
• Support for IAM roles with bulk loading from HAQM Simple Storage Service (HAQM S3)

Launching an HAQM Neptune Cluster

Launching a Neptune cluster is as easy as navigating to the AWS Management Console and clicking create cluster. Of course you can also launch with CloudFormation, the CLI, or the SDKs.

You can monitor your cluster health and the health of individual instances through HAQM CloudWatch and the console.

Additional Resources

We’ve created two repos with some additional tools and examples here. You can expect continuous development on these repos as we add additional tools and examples.

• HAQM Neptune Tools Repo
  This repo has a useful tool for converting GraphML files into Neptune compatible CSVs for bulk loading from S3.
• HAQM Neptune Samples Repo
  This repo has a really cool example of building a collaborative filtering recommendation engine for video game preferences.
  

Purpose Built Databases

There’s an industry trend where we’re moving more and more onto purpose-built databases. Developers and businesses want to access their data in the format that makes the most sense for their applications. As cloud resources make transforming large datasets easier with tools like AWS Glue, we have a lot more options than we used to for accessing our data. With tools like HAQM Redshift, HAQM Athena, HAQM Aurora, HAQM DynamoDB, and more we get to choose the best database for the job or even enable entirely new use-cases. HAQM Neptune is perfect for workloads where the data is highly connected across data rich edges.

I’m really excited about graph databases and I see a huge number of applications. Looking for ideas of cool things to build? I’d love to build a web crawler in AWS Lambda that uses Neptune as the backing store. You could further enrich it by running HAQM Comprehend or HAQM Rekognition on the text and images found and creating a search engine on top of Neptune.

As always, feel free to reach out in the comments or on twitter to provide any feedback!

– Randall