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Building Serverless Apps in AWS with Graph Databases

In this course, *Building Serverless Apps in AWS with Graph Databases*, you’ll learn to deploy a serverless application using Neptune as the database. First, you’ll explore the basics of working with a graph database. Next, you’ll discover to deploy a Neptune stack using serverless. Finally, you’ll learn how to deploy an application and API stack using serverless that communicates with Neptune. When you’re finished with this course, you’ll have the skills and knowledge on how to use Neptune and apply it to your applications.

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Graph Databases Neptune Serverless architecture AWS API Development NOSQL Databases Cloud Security

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Examines Neptune, which is a recommended option for building graph-intensive applications in AWS

Teaches deployment of a serverless application using Neptune as the database

Builds a strong foundation for beginners in the use of Neptune for serverless applications

Taught by Travis Thomsen, an industry expert in the field of graph databases

May require prior knowledge of serverless architectures

May require prior experience with AWS services

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Reviews summary

Practical serverless graph app development on aws

According to students, this course offers a highly practical and relevant deep dive into building serverless applications on AWS using Graph Databases, specifically Neptune. Learners consistently praise the hands-on labs and clear deployment guidance, which provide a complete picture from setup to API integration. While it fills a valuable niche for modern application development, some students note a strong prerequisite knowledge of AWS services like Lambda and API Gateway is crucial. There's a general consensus that the depth on advanced graph concepts or troubleshooting is sometimes light, yet it's an excellent resource for cementing knowledge in this specialized area.

Addresses a specific, highly relevant technology gap.

"Finally a course that shows how to use graph databases in a serverless context!"

"This fills a niche for integrating graph databases into modern serverless applications. Very relevant and up-to-date."

"Valuable content for anyone working with AWS and looking to expand into graph databases."

Focuses on real-world application with effective labs.

"The hands-on labs were incredibly valuable and provided clear, step-by-step guidance."

"Loved the focus on practical deployment. The course provides a complete picture from setting up Neptune to deploying the API."

"The hands-on examples were key to my learning. I feel confident building my own serverless graph applications now."

Potential for outdated setup instructions due to AWS changes.

"Outdated setup instructions. I spent more time debugging old code and matching versions than actually learning."

"I also ran into some environment setup issues that took extra time to debug."

"I would have liked more troubleshooting tips for common AWS deployment errors, as things can get tricky."

Strong on deployment, lighter on advanced graph theory.

"Some parts felt a bit rushed, especially the deeper dives into graph query languages."

"I found some of the explanations for advanced graph concepts a bit light."

"I wish there was more on data modeling for graph databases, but that might be a separate advanced topic."

Requires prior AWS and serverless knowledge for success.

"Make sure you have some prior AWS experience, particularly with Lambda and API Gateway."

"If you're not already comfortable with AWS Lambda, API Gateway, and the Serverless Framework, you'll be lost."

"The prerequisites were not clear enough... Needed much more prior knowledge than I had."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Building Serverless Apps in AWS with Graph Databases with these activities:

Course Materials Organizer

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Stay organized and improve your learning by compiling your course materials.

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Create a dedicated folder for the course
Download all the course materials
Organize the materials into subfolders

Review of Python Basics

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Brush up on your Python skills before taking this course to ensure you have a strong foundation.

Browse courses on Python

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Review the Python documentation
Take a Python practice quiz

Find a Neptune Mentor

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Reach out to a professional or experienced individual who is knowledgeable about Neptune to help you stay motivated and enhance your learning.

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Search online for potential mentors
Attend industry events or conferences
Ask for introductions from your colleagues

Five other activities

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Show all eight activities

Graph Databases: Theory, Algorithms, and Applications

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Reading an in-depth book on graph databases will greatly improve your understanding of the concepts and techniques covered in this course.

View Graph Databases on Amazon

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Purchase the book
Read the book

AWS Immersion Day: Neptune

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Participate in an in-person or virtual hands-on workshop focused on Neptune.

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Register for the event
Attend the workshop
Follow along with the hands-on exercises

Neptune Query Playground

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Practice your Neptune graph querying in order to improve your understanding of Neptune's capabilities as a database.

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Visit the Neptune Query Playground
Explore the sample data
Execute different queries

Neptune Blog Post

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Create a blog post to summarize what you've learned in this course about Neptune.

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Brainstorm topic ideas
Do research and gather information
Write the blog post
Publish your blog post

AWS Neptune Challenge

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Participate in the AWS Neptune Challenge to test your skills and learn from other participants.

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Register for the challenge
Develop your solution
Submit your solution

Career center

Learners who complete Building Serverless Apps in AWS with Graph Databases will develop knowledge and skills that may be useful to these careers:

Software Engineer

A Software Engineer holding an advanced degree, such as this course, would be a strong candidate for work involving serverless applications. Serverless has become increasingly important in the tech industry, and new innovations have made these applications more powerful. Specifically, advancements in graph databases, like the Neptune database used in this course, have given Software Engineers a way to easily query data with complex relationships. This course would help build a foundation for Software Engineers who want to develop these kinds of applications.

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Data Scientist

Similar to Software Engineers, Data Scientists can use this course to learn about advancements in graph databases and serverless application architecture. Advanced graph databases, like Neptune, make it possible to ask complex questions about data. This gives Data Scientists unparalleled insight into their data, which can be highly valuable for a business. This course would provide a Data Scientist with a crucial depth of knowledge that would make them a more competitive candidate for jobs that involve working with graph databases.

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Solutions Architect

A Solutions Architect would benefit from the skills and knowledge provided by this course. Graph databases have a unique set of advantages that can be harnessed to solve problems that relational databases cannot. This course can provide Solutions Architects with an understanding of the strengths and weaknesses of graph databases. In turn, this will help them in recommending the best possible solution for a client's needs. This course will provide a Solutions Architect with the knowledge needed to make the right decision in their next consulting role.

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Database Administrator

A Database Administrator deals with the installation, configuration, maintenance, and performance-tuning of databases. This course would help a Database Administrator understand how to install, configure, and maintain Neptune, a graph database service provided by AWS. This course would also help a Database Administrator understand the performance tuning options available to increase the performance of their database while reducing latency. This knowledge would make a Database Administrator a desirable candidate when applying for jobs.

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DevOps Engineer

A DevOps Engineer would gain valuable knowledge from this course. The cloud-based, serverless implementation of graph databases simplifies DevOps processes considerably. In this course, students will get experience deploying a Neptune stack using serverless and learn to build a continuous integration and continuous delivery (CI/CD) pipeline. With the knowledge and skills learned in this course, a DevOps Engineer will be able to optimize their workflow and increase their efficiency.

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Data Analyst

A Data Analyst may find this course helpful as it teaches students how to build serverless applications using graph databases. This course could be especially helpful for Data Analysts who want to be able to query and analyze data with complex relationships. Graph databases offer a great way to explore connections between data points, and this course will teach students how to use Neptune, a graph database service provided by AWS, to do just that.

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IT Consultant

This course can be helpful for an IT Consultant who wants to learn more about graph databases and serverless applications. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. Serverless applications are also becoming more popular, as they offer a number of benefits over traditional architectures. This course will provide IT Consultants with the skills and knowledge needed to advise their clients on these technologies.

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Cloud Architect

This course will be useful for those looking to become Cloud Architects. Graph databases are becoming increasingly popular for use in the cloud, and serverless applications are a great way to take advantage of the benefits of the cloud. This course will teach Cloud Architects how to deploy a Neptune stack using serverless and how to build a continuous integration and continuous delivery (CI/CD) pipeline. With the knowledge and skills learned in this course, a Cloud Architect will be able to design and implement scalable, reliable, and cost-effective cloud-based solutions.

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Software Developer

This course would be a great fit for Software Developers who want to learn how to build serverless applications using graph databases. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. Serverless applications are also becoming more popular, as they offer a number of benefits over traditional architectures. This course will provide Software Developers with the skills and knowledge needed to develop these kinds of applications.

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Data Engineer

This course could be helpful for those looking to become Data Engineers. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. Serverless applications are also becoming more popular, as they offer a number of benefits over traditional architectures. This course will teach Data Engineers how to deploy a Neptune stack using serverless and how to build a continuous integration and continuous delivery (CI/CD) pipeline. With the knowledge and skills learned in this course, a Data Engineer will be able to design and implement scalable, reliable, and cost-effective data pipelines.

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Systems Analyst

This course will provide Systems Analysts with the skills and knowledge needed to understand the benefits and limitations of graph databases. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. This course will teach Systems Analysts how graph databases can be used to solve complex business problems.

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Technical Architect

This course may be useful for Technical Architects who want to learn how to build serverless applications using graph databases. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. Serverless applications are also becoming more popular, as they offer a number of benefits over traditional architectures. This course will provide Technical Architects with the skills and knowledge needed to design and implement these kinds of applications.

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Business Analyst

This course may be useful for Business Analysts who want to learn how to use graph databases to solve business problems. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. This course will provide Business Analysts with the skills and knowledge needed to understand the benefits and limitations of graph databases and how to use them to solve complex business problems.

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Data Architect

This course may be useful for Data Architects who want to learn how to use graph databases to design and implement data-intensive applications. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and recommendation engines. This course will provide Data Architects with the skills and knowledge needed to understand the benefits and limitations of graph databases and how to use them to design and implement scalable, reliable, and cost-effective data-intensive applications.

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Information Security Analyst

This course may be useful for Information Security Analysts who want to learn how to use graph databases to detect and prevent security breaches. Graph databases are becoming increasingly popular for use cases such as fraud detection, social network analysis, and intrusion detection. This course will provide Information Security Analysts with the skills and knowledge needed to understand the benefits and limitations of graph databases and how to use them to detect and prevent security breaches.

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Reading list

We've selected five books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building Serverless Apps in AWS with Graph Databases.

Graph Databases

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Covers the basics of graph databases. It provides an extensive overview of graph database theory, concepts, and techniques and hence can be used for both background knowledge and as an additional reference.

Graph Databases: New Opportunities for Connected...

Paperback

Graph Databases

Paperback

Graph Databases: New Opportunities for Connected...

Kindle Edition

Machine Learning for Text

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Covers advanced topics in large-scale graph processing, including algorithms, systems, and applications. It explores techniques for handling the challenges of processing massive graph datasets and provides insights into the latest developments in the field.

Machine Learning for Text

Paperback

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Machine Learning for Text

Kindle Edition

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Culture on the Edge of Chaos

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Explores the architecture of knowledge, focusing on the role of networks and systems in organizing and representing knowledge. It offers insights into the theoretical foundations and practical applications of knowledge representation and management, which are relevant to the use of graph databases.

Culture on the Edge of Chaos: Cultural Algorithms...

Paperback

$$$

Advanced Analytics with PySpark

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Covers advanced techniques for analyzing large-scale datasets using Apache Spark. It provides practical guidance on topics such as graph processing, machine learning, and real-time data analysis, making it a valuable resource for data scientists and engineers.

Advanced Analytics with PySpark: Patterns for...

Paperback

Advanced Analytics with PySpark

Kindle Edition

Designing Data-Intensive Applications

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Provides a more advanced look at graph databases, focusing on how to build data-intensive applications. It covers topics such as data modeling, query optimization, and distributed systems.

Designing Data-Intensive Applications: The Big...

Paperback

Designing Data-Intensive Applications: The Big...

Kindle Edition

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