Apache Cassandra

Why a Serverless Data API Might be Your Next Database

Serverless data offers benefits, but market offerings are limited. What serverless data can, should, or could do isn’t always understood.

Backing up K8ssandra with MinIO

K8ssandra includes Medusa for Apache Cassandra® to handle backup and restore for your Cassandra nodes. Recently Medusa was upgraded to introduce support for all S3 compatible backends, including MinIO, the popular k8s-native object storage suite. Let’s see how to set up …

Developing an Enterprise-Level Apache Cassandra Sink Connector for Apache Pulsar

Streaming with Apache Pulsar: connecting existing enterprise data sources to Apache Cassandra using Pulsar.

K8ssandra: Production-Ready Platform for Running Apache Cassandra on Kubernetes

K8ssandra aims to provide a “production-ready platform”, and this includes automation for operational tasks such as repairs, backups, and monitoring.

K8ssandra Performance Benchmarks on Cloud Managed Kubernetes

Running Cassandra in Kubernetes using K8ssandra does not introduce any notable performance impacts in throughput nor in latency.

We were thrilled to see that K8ssandra dramatically simplified the deployment of Cassandra clusters, making it mostly transparent to run on premises or on cloud managed Kubernetes services, while offering the same level of performance. 

Connect Stateful Workloads Across Kubernetes Clusters

Learn how, with a bit of creativity, we were able to utilize off-the-shelf functionality and components to set up lightweight cross-cluster communication for apps in a multitenant environment.

While this solution is applicable to a somewhat narrow use case, it does come with several important advantages, including shared-nothing architecture, low complexity, low operational burden, and high degree of isolation between tenants.

The Search for a Cloud-Native Database

A cloud-native database is one that is designed with cloud-native principles in mind, including scalability, elasticity, resiliency, observability, and automation.

As we’ve seen with Cassandra, automation is often the final milestone to be achieved, but running databases in Kubernetes can actually help us progress toward this goal of automation.

What’s next in the maturation of cloud-native databases? We’d love to hear your input as we continue to invent the future of this technology together.

Best Practices for Data Pipeline Error Handling in Apache NiFi

We have tools such as Apache NiFi, which allow us to design and manage our data pipelines, reducing the amount of custom programming and increasing overall efficiency.

Yet, when it comes to creating them, a key and often neglected aspect is minimizing potential errors.

Although many factors influence a NiFi data pipeline, three important ones are: understanding the nature of your data sources and targets, minimizing maintenance, and following best practices.

A Case for Databases on Kubernetes from a Former Skeptic

Looking back at the pitfalls of running databases on Kubernetes I encountered several years ago, most of them have been resolved.

All of these problems are hard and require technical finesse and careful thinking. Without choosing the right pieces, we’ll end up resigning both databases and Kubernetes to niche roles in our infrastructure, as well as the innovative engineers who have invested so much effort in building out all of these pieces and runbooks.

Why Kubernetes Is The Best Technology For Running A Cloud-Native Database

Must a database run on Kubernetes to be considered cloud-native?

While Kubernetes was originally designed for stateless workloads, recent improvements in Kubernetes such as StatefulSets and persistent volumes have made it possible to run stateful workloads as well. Even longtime DevOps practitioners skeptical of running databases on Kubernetes are beginning to come around, and best practices are starting to emerge.

Apache Cassandra 4.0: Taming Tail Latencies with Java 16 ZGC

With Apache Cassandra 4.0, you not only get the direct improvements to performance added by the Apache Cassandra committers, you also unlock the ability to take advantage of seven years of improvements in the JVM itself.

This article focuses on improvements in Java garbage collection that Cassandra 4.0 coupled with Java 16 offers over Cassandra 3.11 on Java 8.