Cassandra

Definition

Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of structured data across many commodity servers. It offers high availability with no single point of failure, making it ideal for applications requiring continuous uptime and quick data access. Its architecture is based on a peer-to-peer model, where all nodes are equal and can handle read and write requests, connecting seamlessly to efficiently manage big data environments.

5 Must Know Facts For Your Next Test

1. Cassandra was originally developed at Facebook to power its inbox search feature, highlighting its capability to handle large volumes of data.
2. It uses a flexible data model that allows for dynamic addition of columns to tables without downtime, catering to evolving data requirements.
3. Cassandra employs tunable consistency, allowing developers to balance between performance and the level of consistency needed for their applications.
4. Data in Cassandra is organized into column families, which store rows by unique keys, making it efficient for retrieving large datasets based on specific queries.
5. The database supports horizontal scaling by adding more nodes without requiring significant changes to the existing infrastructure or schema.

Review Questions

• How does Cassandra's architecture contribute to its ability to maintain high availability and scalability?
  • Cassandra's architecture is built on a peer-to-peer model, meaning every node in the cluster can accept requests without relying on a single master node. This structure eliminates any single points of failure, ensuring that if one node goes down, others continue to serve requests. Additionally, its ability to scale horizontally allows organizations to add more nodes seamlessly, which enhances both capacity and performance as data volumes grow.
• Discuss the significance of tunable consistency in Cassandra and how it impacts application performance.
  • Tunable consistency in Cassandra allows developers to choose the level of consistency required for their applications based on specific needs. This means that users can configure whether they want strong consistency (where all nodes must acknowledge a write) or eventual consistency (where updates are propagated over time). This flexibility enables applications to optimize performance by choosing lower consistency levels during peak loads while maintaining higher levels when necessary for critical transactions.
• Evaluate the advantages and challenges of using Cassandra as a NoSQL solution for big data applications.
  • Using Cassandra as a NoSQL solution offers several advantages, including its ability to handle massive amounts of data across distributed systems with high availability and fault tolerance. Its flexible schema allows for easy adjustments as data needs change. However, challenges include the complexity of managing a distributed system and understanding its eventual consistency model, which can lead to confusion when ensuring data accuracy during updates. Balancing these benefits and challenges is key for organizations considering Cassandra for their big data applications.

Related terms

NoSQL: A category of database systems that provides 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 is spread across multiple sites or nodes, allowing for better scalability and reliability.

Data Replication: The process of storing copies of data on multiple nodes to ensure redundancy and improve data availability and access speed.