Solutions using Elasticsearch

Graph databases leverage the connections that exist in your data to provide further insight into what your data actually means. JanusGraph in particular can be connected to a Cassandra DB backend and Elasticsearch for indexing, making it an obvious choice when dealing with distributed data pipelines. View on Github

Distributed apps quickly get to the place where trying to debug using tail -f becomes untenable. However, ignoring your logs isn't an option. The ELK Stack (Elasticsearch, Logstash, and Kibana) is a go-to tool for managing your logs and making them help you rather than just taking up hard drive space. Unfortunately, it does not yet have out-of-the-box log processing or dashboards for Cassandra. Check out a way to extract meaningful information from your Cassandra logs here. 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