Introduction to Apache Cassandra

Apache Cassandra is a highly scalable and distributed NoSQL database system. It was developed by Facebook in 2008 and opened source in 2010, and is currently maintained by the Apache Software Foundation. Cassandra is designed to handle large-scale datasets and applications with high availability requirements, and it has horizontal scalability and fault tolerance. Cassandra is suitable for scenarios that require large capacity and high-performance Distributed database, especially for applications that need to write and read large amounts of data quickly. Common application scenarios include log analysis, time series data storage, social networks, network recommendations, and the Internet of Things. The main advantages of Cassandra include the following: 1. Distributed architecture: Cassandra adopts a distributed data storage and replication mechanism, which can distribute data on hundreds of servers, providing high availability and scalability. 2. Fast read and write: Cassandra adopts a storage engine based on log structure, which can provide high performance in write and read operations. 3. Fault tolerance and high availability: Cassandra supports redundant replication of data and automatic fault recovery, allowing it to continue providing services even in the event of partial node failures. Some of Cassandra's drawbacks include: 1. Data consistency: Cassandra adopts the Eventual consistency model, that is, it does not guarantee strong consistency of data among all nodes. For some applications requiring strong consistency, additional work may be required to solve this problem. 2. High storage space requirements: Cassandra replicates data on multiple servers to provide fault tolerance. This makes Cassandra's storage requirements relatively high. 3. Complexity: Cassandra is relatively complex in terms of configuration and management, requiring some learning and experience. Cassandra's technical principle is based on a distributed Hash table, which distributes data evenly across multiple nodes through a consistent hash algorithm. It adopts a peer-to-peer replication architecture without a central node, and each node can run independently and process read and write requests. Cassandra also supports multiple data centers and cross regional replication, providing flexible data storage and redundancy strategies. For performance analysis, Cassandra has the following key indicators: 1. Throughput: Cassandra can provide high write and read throughput, especially suitable for scenarios that require processing large amounts of data and high concurrency of reads and writes. 2. Latency: Cassandra typically provides low latency read and write operations. The size of latency is influenced by a series of factors, such as data model design, hardware configuration, and load conditions. Cassandra's official website is: https://cassandra.apache.org/ Summary: Apache Cassandra is a highly scalable and distributed NoSQL database system suitable for applications with large-scale datasets and high availability requirements. It has advantages such as distributed architecture, fast read/write, fault tolerance, and high availability, but there are some drawbacks in terms of data consistency, storage space requirements, and complexity. Cassandra's technical principle is based on a distributed Hash table, which uses a consistent hash algorithm to distribute data on multiple nodes. In terms of performance, Cassandra has the characteristics of high throughput and low latency.