Cassandra is a popular NoSQL database that is known for its scalability and high availability. However, like any technology, it has its limitations. In this article, we will explore some of the key limitations of Cassandra DB that developers should be aware of.

Data Modeling Limitations

One of the main limitations of Cassandra is its data modeling capabilities. While Cassandra is great for write-heavy workloads, it can be challenging to design data models for complex queries that involve multiple tables or relationships.

No Support for Joins

Cassandra does not support joins, which can make it difficult to model data that requires relationships between multiple tables. Developers have to denormalize data or perform multiple queries to achieve the same result, which can impact performance.

Limited Support for Secondary Indexes

While Cassandra does support secondary indexes, they are limited in functionality compared to traditional relational databases. Secondary indexes can only be created on a single column and are not suitable for all types of queries.

Consistency and Performance Limitations

Another limitation of Cassandra is its consistency and performance characteristics. While Cassandra is designed to be highly available, achieving strong consistency can be challenging.

Eventual Consistency Model

Cassandra uses an eventual consistency model, which means that changes to data may take some time to propagate across all nodes in the cluster. This can lead to inconsistencies in data when performing read operations immediately after a write.

Performance Impact of Compaction

Compaction is a process in Cassandra that merges multiple SSTables to improve read performance. However, compaction can be resource-intensive and impact the performance of the cluster, especially during peak usage times.

Operational Limitations

Finally, Cassandra also has operational limitations that developers should consider when deploying and managing a Cassandra cluster.

Complex Deployment and Configuration

Setting up and configuring a Cassandra cluster can be complex, especially for developers who are new to the technology. Managing replication strategies, partitioning, and consistency levels requires a deep understanding of Cassandra’s architecture.

Hardware Requirements

Cassandra is designed to run on a distributed cluster of commodity hardware. While this can be cost-effective, it also means that developers need to carefully plan their hardware requirements to ensure optimal performance and scalability.

While Cassandra is a powerful database system, it is important for developers to be aware of its limitations in order to make informed decisions when choosing a database solution for their applications.