Cassandra vs PostgreSQL: What are the differences?

Comparison between Cassandra and PostgreSQL

Cassandra and PostgreSQL are both widely used and popular database management systems. However, they have significant differences in terms of their architecture, data model, scalability, query language, and ACID compliance.

1. Architecture: Cassandra is a distributed database that follows a peer-to-peer architecture, whereas PostgreSQL follows a client-server architecture. Cassandra allows data to be distributed across multiple nodes, ensuring high availability and fault tolerance. In contrast, PostgreSQL relies on a single server for data storage and processing.

2. Data Model: Cassandra is based on a NoSQL data model, specifically a wide-column store. It allows for flexible schema-less data storage where each row can have a different number of columns. On the other hand, PostgreSQL follows a relational data model, where data is organized into tables with predefined schemas and relationships between them.

3. Scalability: Cassandra is designed to scale horizontally by adding more nodes to the cluster. It can handle high write and read throughput by distributing data evenly across the nodes. PostgreSQL, however, is primarily designed to scale vertically by increasing the resources of the server. It relies on a single server's hardware capabilities to handle the workload.

4. Query Language: Cassandra uses CQL (Cassandra Query Language), which is similar to SQL but has some differences. CQL is optimized for distributed databases and provides a more flexible and less expressive query language compared to PostgreSQL's SQL. PostgreSQL, as a relational database, uses SQL (Structured Query Language) for data manipulation and retrieval.

5. ACID Compliance: ACID (Atomicity, Consistency, Isolation, Durability) is a set of properties that ensure database transactions are reliable. PostgreSQL is ACID-compliant, meaning it guarantees the integrity and consistency of transactions. In contrast, Cassandra sacrifices full ACID compliance for higher scalability and performance. It guarantees eventual consistency, where updates are propagated asynchronously to maintain system availability.

6. Use Cases: Due to their architectural differences and design choices, Cassandra is well-suited for handling massive amounts of data, particularly in distributed and highly available systems. It excels in use cases that require horizontal scalability, such as IoT databases, real-time analytics, and time series data. PostgreSQL, on the other hand, is a versatile database that fits well in applications that require complex joins, transactions, and SQL-based querying.

In summary, Cassandra and PostgreSQL differ in their architecture, data model, scalability, query language, ACID compliance, and use cases. While Cassandra focuses on high scalability and fault tolerance, PostgreSQL offers a more traditional approach with full ACID compliance and advanced SQL querying capabilities.