Solutions using Gatsby

The strength of a full-stack data engineer is the ability to bring the entire stack together, coordinating all of your microservices and features into a single product. Any developer can slap a new feature onto your project, but if new features aren't seamlessly integrated into your project as a whole, they will run inefficiently and slow down future development. See how everything can work together, from data pipeline to web app to data visualization and user-facing search functionality. View on Github

Data visualization is particularly valuable when it comes to graph processing. If you are using graph technology due to the connectivity within your data, then you will want to visualize the connectivity and show it to your clients. Vega, being built on D3.js, comes with a powerful API to do just that. View on Github

Elassandra makes it easy to quickly and easily use Cassandra together with Elasticsearch, allowing us to take advantage of the strength of each. With a simple NodeJS server on top of that, and tools like React and Searchkit, we can access and display our data whether it originated in Cassandra or Elasticsearch. If you have a Cassandra cluster and want to add greater querying power, or on the other hand have Elasticsearch and want to pair it with the capabilities of Cassandra, it’s definitely worth giving Elassandra a look. View on Github

Your data won't help you if you don't know how to use it. One way is to allow end-users (or admins) to search through your data. Elassandra integrates Elasticsearch with your Cassandra DB for near instant search results and a REST API. One way to access that REST API is by connecting to it through a React app, with a Flask app server in the middle to handle requests. Click here to get an idea for how I can build a similar solution for your app. View on Github