Understanding the Basics of Apache Cassandra

Cassandra Summit 2016 took place recently in San Jose, California. The Cassandra Summit is a conference for those who are looking to learn more about adopting DataStax’s Apache Cassandra, the scalable NoSQL database that powers global businesses like Spotify, Netflix, and Apple. Couldn’t make it out to San Jose for the conference this year? We’ll fill you in.

Apache Cassandra is a NoSQL, or “non-relational,” database. In today’s world, many online applications have database requirements that exceed the capabilities of traditional databases. Non-relational databases were created to meet these requirements. They have very low latency, and can adapt to unknown levels of scale while providing “continuous uptime, global distribution of data, and the ability to both write and read data anywhere,” which reduces software and operational costs. Apache Cassandra is considered a non-relational database because it provides “a massively scalable open source database offering continuous availability, linear scale performance, operational simplicity, and easy data distribution across multiple data centers and cloud availability zones.”

Cassandra’s “ring” architecture is masterless, meaning all nodes play an identical role instead of having one master node. These nodes communicate with each other via a “distributed, scalable protocol called ‘gossip.’” This architecture is specifically designed for scale, and it is capable of “handling large amounts of data and thousands of concurrent users or operations per second just as easily as it can manage smaller amounts of data and user traffic.” The ring architecture also means that there is no single point of failure, meaning availability and uptime can be truly continuous.

These features make Apache Cassandra a popular choice for enterprises looking for both scalability and high-availability without compromising performance. Since all nodes in Cassandra’s architecture design are the same, enterprises can create databases that are both massively scalable and operationally simple. It’s flexible and dynamic data model easily supports modern data types, and data can be compressed up to 80% without compromising performance. The ability to scale by adding nodes into an existing ring without having to take it down first allows for predictable increases in performance that can be replicated across multiple data centers.

The Cassandra database is especially useful for enterprises developing internet of things applications, messaging platforms, and social media analytics and recommendation engines. Media companies, like Spotify, use Cassandra to track and monitor the activity of their users’ activity and interactions on their applications so they can tailor content recommendations to each specific user. Cassandra is also a popular choice for online retailers looking to provide customers with reliable shopping cart security and retail app support.

Datapipe supports NoSQL database employments for our clients, and proudly partners with DataStax to offer an enterprise grade, production ready Apache Cassandra offering, which can be supported on AWS and Azure. For more information on Datapipe’s database services, visit our website. If you’re interested in learning more about Cassandra, DataStax recommends taking their free course, DS201: Foundations of Apache Cassandra.

To learn more about deploying Cassandra on Amazon Web Services and Azure please visit the following resources:

Cassandra on AWS

Cassandra on Azure


David Lucky is a Product Marketing leader at Rackspace for the Managed Public Cloud services group, a global business unit focused on delivering end-to-end digital transformation services on AWS, Azure, GCP and Alibaba. David came to Rackspace from Datapipe where as Director of Product Management for six years he led product development in building services to help enterprise clients leverage managed IT services to solve complex business challenges. David has unique insight into the latest product developments for private, public and hybrid cloud platforms and a keen understanding of industry trends and their impact on business development. He holds an engineering degree from Lehigh University and is based out of Jersey City, NJ. You can follow David on LinkedIn at linkedin.com/in/davidlucky and Twitter @Luckys_Blog.