Cassandra

Definition

Cassandra is a highly scalable and distributed NoSQL database designed to handle large amounts of structured data across many commodity servers. It excels in providing high availability with no single point of failure, making it a popular choice for applications requiring robust performance and reliability, especially in the context of cloud computing and big data applications.

5 Must Know Facts For Your Next Test

1. Cassandra was originally developed at Facebook to handle their inbox search feature and was released as an open-source project in 2008.
2. It uses a peer-to-peer architecture, meaning every node in the cluster has the same role, which contributes to its high availability and scalability.
3. Cassandra is designed to handle write-heavy workloads, making it ideal for applications that require real-time analytics and quick data ingestion.
4. It supports flexible schema design with its wide-column store approach, allowing for dynamic addition of columns and rows without downtime.
5. The database implements tunable consistency, allowing developers to choose the level of consistency required for their applications, balancing between consistency and availability.

Review Questions

• How does Cassandra's architecture contribute to its scalability and availability?
  • Cassandra's architecture is based on a peer-to-peer model where each node in the cluster has equal responsibilities. This eliminates single points of failure, enabling high availability since any node can accept read or write requests. Additionally, data is distributed evenly across all nodes using consistent hashing, which allows the system to easily scale horizontally by adding more nodes without disrupting existing operations.
• Discuss how Cassandra handles data consistency and what role eventual consistency plays in its operation.
  • Cassandra implements eventual consistency as part of its distributed architecture, meaning that while immediate consistency is not guaranteed across all nodes after a write operation, all replicas will eventually converge to the same value. This model allows Cassandra to prioritize availability and partition tolerance over strong consistency, making it suitable for applications where it’s acceptable for data to be slightly out-of-sync temporarily.
• Evaluate the use cases where Cassandra would be preferred over traditional relational databases, especially considering its strengths and limitations.
  • Cassandra is particularly well-suited for use cases involving large volumes of write operations, such as social media feeds, real-time analytics, and IoT applications where high throughput and low latency are critical. Unlike traditional relational databases, which may struggle with scalability when faced with vast datasets or high-velocity data streams, Cassandra’s distributed nature allows it to maintain performance as the workload grows. However, its trade-offs include less emphasis on complex querying capabilities and transaction support compared to SQL-based systems.

Related terms

NoSQL: A category of databases that provide a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.

Distributed Database: A database that is not stored in a single location but rather spread across multiple physical locations, which can help with redundancy and scalability.

Eventual Consistency: A consistency model used in distributed systems that allows for temporary inconsistencies, with the guarantee that all changes will eventually propagate to all nodes.