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Ans. Cassandra architecture refers to the structure and design of the Apache Cassandra database system. It is a distributed, highly scalable, and fault-tolerant system that follows a peer-to-peer architecture. Cassandra uses a ring-like structure where data is distributed across multiple nodes in a cluster, allowing for horizontal scalability and high availability.

Ans. Apache Cassandra is a highly popular and widely used NoSQL database management system. It offers several benefits, including: - Scalability: Cassandra can easily handle large amounts of data and scale horizontally by adding more nodes to the cluster. - High availability: It provides fault-tolerance and replication of data across multiple nodes, ensuring high availability even in the event of node failures. - Performance: Cassandra offers fast read and write operations due to its distributed architecture and efficient data storage model. - Flexibility: It supports flexible data models and schema-less design, allowing for easy adaptation to changing business requirements. - Ease of use: Cassandra is easy to set up, configure, and manage, making it a popular choice for database management.

Ans. The key components of Cassandra architecture include: - Node: It is an individual server that stores data and participates in the cluster. - Datacenter: It is a collection of nodes that are grouped together and located in the same physical location. - Cluster: It is a collection of multiple datacenters that work together. - Commit log: It is a file that stores write operations before they are written to the disk. - Memtable: It is a data structure in memory where write operations are initially stored before being flushed to disk. - SSTables: Immutable on-disk data files that store the actual data in Cassandra. - Replication: It is the process of copying data across multiple nodes for fault-tolerance and high availability.

Ans. Cassandra ensures data consistency and fault-tolerance through the following mechanisms: - Replication: Cassandra replicates data across multiple nodes in a cluster, ensuring that copies of data are available on different machines. This provides fault-tolerance and prevents data loss in the event of node failures. - Consistency level: Cassandra allows users to specify the level of consistency required for read and write operations. Consistency levels determine how many replicas need to respond to a request before it is considered successful, ensuring data consistency across the cluster. - Hinted handoff: In case a node is temporarily unavailable, Cassandra stores hints about the missed writes and delivers them to the node once it becomes available again, ensuring data consistency. - Read repair: Cassandra automatically detects inconsistencies during read operations and repairs them by updating replicas with the latest data.

Ans. Yes, Cassandra is designed to handle large-scale data sets. It can easily handle terabytes or even petabytes of data. Cassandra's distributed architecture allows it to scale horizontally by adding more nodes to the cluster, enabling seamless expansion as data volume increases. Additionally, Cassandra's data partitioning and replication mechanisms ensure efficient storage and retrieval of large amounts of data across multiple nodes in a cluster.