Introduction to Cassandra Database: Key Concepts

15.01.2025

Understanding Cassandra Database: Key Concepts

Intro to NoSQL with Apache Cassandra - YouTube

1. NoSQL Database

Introduction to NoSQL • Martin Fowler • GOTO 2012 – YouTube
Feb 19, 2013 … … important consequence of polyglot persistence. TIMECODES 00:00 Intro 00:42 History of NoSQL databases 07:51 Definition of NoSQL 09:36 Data model …

Cassandra is a NoSQL database that provides a highly scalable, distributed, and fault-tolerant data storage solution. Unlike traditional SQL databases, NoSQL databases like Cassandra are designed to handle large amounts of data across multiple servers.

2. Distributed Architecture

Cassandra uses a decentralized architecture where data is distributed across multiple nodes in a cluster. Each node in the cluster is independent and communicates with other nodes using a peer-to-peer protocol. This distributed architecture allows Cassandra to scale horizontally by adding more nodes to the cluster.

3. Data Model

Cassandra is a column-family database that stores data in rows and columns. Each row is identified by a unique key, and columns are grouped together into column families. The flexible schema of Cassandra allows each row to have a different number of columns, making it suitable for storing semi-structured and unstructured data.

4. CAP Theorem

Cassandra is designed based on the CAP theorem, which states that a distributed system can only guarantee two out of three properties: consistency, availability, and partition tolerance. Cassandra chooses availability and partition tolerance over strong consistency, making it an eventually consistent database.

5. Replication

Cassandra uses replication to ensure data durability and fault tolerance. Data is replicated across multiple nodes in the cluster, allowing Cassandra to continue functioning even if some nodes fail. Replication also improves read performance by serving read requests from multiple replicas.

6. Partitioning

Cassandra partitions data using a consistent hashing algorithm, where each row is assigned to a specific node based on its partition key. This allows Cassandra to distribute data evenly across the cluster and ensures that queries can be executed efficiently by targeting specific nodes.

7. Consistency Levels

Cassandra provides tunable consistency levels that allow developers to control the trade-off between consistency and availability. Consistency levels can be set at the query level, allowing developers to choose the level of consistency required for each operation.

8. Query Language

Cassandra uses CQL (Cassandra Query Language) as its query language, which is similar to SQL but optimized for the distributed nature of Cassandra. CQL allows developers to interact with Cassandra using familiar SQL-like syntax for creating tables, querying data, and managing the database.

9. Use Cases

Cassandra is well-suited for use cases that require high availability, scalability, and fault tolerance. It is commonly used for time-series data, real-time analytics, and applications that need to handle large amounts of data across multiple data centers.

10. Conclusion

Understanding the key concepts of Cassandra, such as its distributed architecture, data model, and consistency model, is essential for building scalable and reliable applications. By leveraging the features of Cassandra, developers can design data-intensive applications that can handle the demands of modern web applications.

Yan Hadzhyisky

fullstack PHP+JS+REACT developer