Apache Cassandra is an open-source, NoSQL database that allows users to manage massive amounts of data quickly and stress-free.

Are you interested in trying out Cassandra? Are you curious about its benefits and drawbacks?

If so, you’re in the right place. Discover everything you need to know about Cassandra below.

What Is Cassandra?

Apache Cassandra is an open-source, NoSQL distributed database.

Thousands of companies worldwide use and trust this because of its scalability, high availability, and consistent performance. It offers users linear scalability and proven fault tolerance on both commodity hardware and cloud infrastructure.

Cassandra Ecosystem

The Cassandra Ecosystem includes a wide range of third-party projects, tools, products, and services for end users. The following are just some of the solutions available in the ecosystem:

  • Aiven: A fully managed NoSQL database that can be deployed in the cloud of your choice.
  • Amazon Keyspaces: A scalable, highly functional, and managed Cassandra–compatible database service.
  • DataStax Desktop: A cross-platform (Windows, macOS, Linux) application that allows developers to explore Cassandra more quickly.
  • Apache Ignite: Can be used as a traditional SQL database with the help of JDBC drivers, ODBC drivers, and native SQL APIs available for Java, C#, C++, Python, etc.
  • Confluent Connect Cassandra: Used to move messages from Apache Kafka into Apache Cassandra.

Getting Started with Cassandra

Those who want to start using Cassandra and exploring the Ecosystem can do so in just a few steps:

  1. Get Cassandra as a tarball or package download with Docker Desktop.
  2. Start Cassandra.
  3. Create files using Cassandra Query Language (CQL) — similar to SQL but better suited to Cassandra’s JOINless structure.
  4. Load data with the CQL shell (or CQLSH).
  5. Use CQLSH to run CQL commands interactively.
  6. Read and write data.
  7. Clean up data.

Cassandra Pros

There are many reasons why businesses worldwide use Cassandra and the tools that make up the Cassandra Ecosystem. The following are some of the most frequently cited pros Cassandra offers:

Fault Tolerance

One of Cassandra’s greatest assets is its fault tolerance. It replicates across multiple data centers and can survive regional outages with ease. You can replace failed nodes without downtime, too.

Quality Assurance Testing

Cassandra has been thoroughly tested to ensure stability and reliability. It’s been tested on clusters of up to 1,000 nodes with a focus on replay, property-based, fault-injection, fuzz, and performance tests.

Superior Performance

In tests, it consistently outperforms other popular NoSQL alternatives — primarily due to superior fundamental architectural choices.

User Control

With Cassandra, users can choose between synchronous and asynchronous replication for each update.

Security and Observability Features

It is a highly secure option. It includes an audit logging feature that tracks DML, DDL, and DCL activity with little effect on workload performance. The fqltool allows users to capture and replay production workloads for in-depth analyses.

Scalability

It also allows users to scale their operations quickly. Read and write throughput increase linearly whenever new machines are added, and users don’t have to worry about downtime or interruption to existing applications.

Elasticity

Users also appreciate its elasticity, especially in cloud and Kubernetes environments. The platform streams data between nodes using zero-copy streaming, which makes the process up to five times faster.

Cassandra Cons

Although it offers many benefits, it also comes with some downsides and is not sufficient for all businesses. Here are some cons to consider before jumping on the bandwagon:

No Support for ACID Properties

It does not support ACID and relational data properties, so it won’t work for users that rely heavily on these.

No Support for Aggregates

The same goes for aggregates. If you do a lot of them, another database will work better.

Latency

It comes with some latency issues. These issues stem from making excessive requests and reading more data, both of which will slow down the transaction.

Potential Join Issues

It doesn’t come with join or subquery support, which can affect the performance and increase the overhead.

Reads Are Slower in Cassandra

It was optimized for fast writes, whereas reads were less of a concern.

Potential JVM Memory Management Issues:

It also requires JVM to store vast amounts of data; Garbage collection isn’t performed by the application but bCy, a language within the platform.

How Can Cassandra Be Used for Business Intelligence?

Cassandra is widespread throughout the business intelligence world for numerous reasons. The following are some of the most well-known reasons why BI professionals choose it over other options:

Speed and Scalability

Efficiency is of the essence for most BI professionals, and its unique architectural structures allow for maximum speed and more streamlined scaling.

Its speed is primarily attributed to two features: A hashing algorithm that allows it to make rapid storage decisions, and independence for nodes that make data storage decisions, meaning there’s no centralized “master node” that controls all storage decisions.

Fault Tolerance

Like many other Apache systems, it is known for its fault tolerance. It provides peace of mind with its masterless design. Because no single point of failure exists and because Cassandra enables data replication through multiple data centers, you can feel confident that your data is secure no matter what happens.

Customization

Regardless of their specific company needs and goals, BI professionals can use this to meet and accomplish them. It can easily be customized for numerous environments. For example, if much of your log data is read infrequently, you can adjust the configuration for write-heavy systems.

Integration

It easily integrates with numerous core systems. If you already utilize other Apache tools, such as Apache Spark, Kafka, Mahout, or Solr, you’ll have no trouble incorporating Cassandra into the mix.

Social Proof

It has a proven track record with case studies from various businesses, from startups to some of the world’s largest enterprises.

A year ago, Apple revealed that it was running over 75,000 Cassandra nodes and storing over 10 petabytes of data. Netflix also manages several petabytes of data in there.

Discord recently announced that it was the only database that fulfilled all of its requirements — precisely because it’s easy to add nodes and because the loss of nodes doesn’t interfere with the application’s performance.

How Yurbi Can Help with Cassandra

So here’s the thing: Yurbi has no native integrations yet for Cassandra as a data source, but we can integrate it through third-party ODBC drivers.

Yurbi is not able to directly communicate with Cassandra through their CQL, but it can support 3rd party ODBC drivers that allow communication with it in a similar way to a relational database. Examples of such drivers include CDATA and Progress.

In addition, Yurbi can provide the ability to combine data from Cassandra with data from other data sources into single reports and dashboards. It can also provide users the ability to query and pull data without needing access directly to Cassandra or requiring technical skills in writing queries.

Yurbi is a self-service BI tool that can complete the presentation layer of your BI tech stack.

Yurbi provides ad-hoc query capability, data merging, data visualization, embedded analytics, and modern business intelligence in general. With its reasonable price points, small and medium-sized enterprises can digitize and optimize their businesses with Yurbi.

Hop on a meeting with us or take advantage of our free live demo sessions to see how we roll.