Cassandra Architecture

1. Distributed Architecture:

• Peer-to-Peer Model:

  • Cassandra follows a peer-to-peer distributed architecture, where all nodes in the cluster are equal and communicate with each other directly.
  • There are no dedicated master or coordinator nodes, eliminating single points of failure and bottlenecks.

• Ring Topology:

  • Cassandra uses a ring topology, where each node in the cluster communicates with its adjacent nodes to form a logical ring.
  • Data is partitioned and distributed across nodes in the ring based on consistent hashing.

2. Replication and Partitioning:

• Partitioning:
  • Data in Cassandra is partitioned across the cluster based on the hash value of the partition key.
  • Each node is responsible for a range of data partitions, ensuring uniform distribution and load balancing.
• Replication:
  • Cassandra replicates data across multiple nodes to ensure fault tolerance and high availability.
  • Replication strategies define how many replicas of each data partition are stored and on which nodes they reside.

3. Data Model:

• Wide Column Store:
  • Cassandra uses a wide column store data model, also known as the column-family model.
  • Data is organized into tables with rows identified by a primary key, consisting of a partition key and optional clustering columns.
  • Columns within rows are grouped into column families, providing flexibility in schema design.

4. Gossip Protocol:

• Peer Discovery:
  • Cassandra uses a gossip protocol for peer discovery and communication among nodes.
  • Nodes periodically exchange state information about themselves and other nodes in the cluster, enabling dynamic cluster membership and failure detection.

5. CAP Theorem:

• Consistency, Availability, Partition Tolerance:
  • Cassandra is designed to provide both eventual consistency and high availability in the presence of network partitions (CAP theorem).
  • Tunable consistency levels allow developers to balance consistency, availability, and partition tolerance based on application requirements.

6. Read and Write Operations:

• Write Path:

  • Write operations in Cassandra are first written to a commit log for durability and then to an in-memory data structure called a memtable.
  • Periodically, memtables are flushed to disk as immutable SSTables (Sorted String Tables).

• Read Path:

  • Read operations involve querying one or more replicas of the requested data partition.
  • Cassandra supports tunable consistency levels for read operations, allowing developers to specify the level of consistency required for each read.

7. Architecture Components:

• Node:

  • A physical or virtual server running Cassandra software, responsible for storing data and participating in cluster operations.

• Datacenter:

  • A group of related nodes located within the same geographical region or network infrastructure.
  • Cassandra supports multi-datacenter deployments for geographical redundancy and disaster recovery.

• Cluster:

  • A cluster consists of one or more interconnected nodes sharing the same logical Cassandra instance.
  • It spans multiple datacenters and is managed as a single entity.

Summary:

Cassandra's architecture is designed to provide a distributed, fault-tolerant, and scalable platform for managing large volumes of data. Its decentralized peer-to-peer model, partitioning and replication strategies, wide column store data model, and support for tunable consistency levels make it well-suited for high-performance, distributed database applications.