In this installment of the MMS series, we take a look at how to store binary blobs into a Scylla cluster using the Java programming language.
We recently hosted the webinar, Steering the Sea Monster: Integrating Scylla with Kubernetes. We received a lot of great questions during the live webinar, so here they are along with our answers. Miss the live webinar? You can access the on-demand version here.
Division 3 now wants to dive back into data analytics to learn how to prevent the attacks. In this installment of the Mutant Monitoring series, we take a look at how to use Apache Spark, Hive, and Superset to analyze and visualize data from the Mutant Monitoring System.
In this installment of the MMS series, we take a look at Materialized Views. Material Views automate the tedious and inefficient work that must be done when an application maintains several tables with the same data that’s organized differently.
Prepared statements enable developers to optimize their applications more efficiently. In this installment of the Mutant Monitoring Series, learn how to use prepared statements with the Java Cassandra driver on a Scylla cluster.
Division 3 decided that we must use more applications to connect to the mutant catalog and decided to hire Java developers to create powerful applications that can monitor the mutants. In this post, we will explore how to connect to a Scylla cluster using the Cassandra driver for Java.
In the Day 6 post, we expanded the initial Mutant Monitoring Scylla Cluster from one to two datacenters. Now we must begin to learn more about how to work with our data in such a setup. In this post, you will learn more about the consistency level options available when using Scylla with multiple datacenters.
This is the first of the Mutant Monitoring System series. In this post, we set up a Scylla cluster in Docker and create the initial keyspace for the Mutant Catalog.
The combination of a database and full-text search analytics becomes unavoidable these days. In this blog post, I will demonstrate a simple way to analyze data from a database with analytics software by using Scylla and Elasticsearch together to perform a simple data mining exercise that gathers data from Twitter. This demonstration will use a series of Docker containers that will run a Scylla and Elasticsearch cluster and a Node.js app that will feed data from Twitter into both platforms. This demo can be run on a laptop or production Docker server. To get started, let’s go over the prerequisites […]
This blog post is a short introduction on how to use the ScyllaDB Docker image to start up a Scylla node, access nodetool and cqlsh utilities, start a cluster of Scylla nodes, configure data volume for storage, and configure resource limits of the Docker container. For full documentation, see the image description on Docker Hub.