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Apache Cassandra vs PostgreSQL
June 04, 2023 | Author: Michael Stromann
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Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients.
Apache Cassandra and PostgreSQL are both popular open-source database management systems, but they differ in their data models, scalability, querying capabilities, and consistency models.
Apache Cassandra is a highly scalable and distributed NoSQL database designed for handling large amounts of data across multiple commodity servers. It follows a wide-column data model and provides high availability and fault tolerance through its masterless architecture. Cassandra is known for its ability to handle massive write and read workloads, making it suitable for applications that require high scalability and low-latency data access. However, it sacrifices some features of traditional databases, such as complex joins and transactions, in favor of scalability and performance.
PostgreSQL, on the other hand, is a powerful relational database management system (RDBMS) known for its robustness and compliance with the SQL standard. It supports ACID (Atomicity, Consistency, Isolation, Durability) properties and offers a wide range of advanced features, including complex queries, joins, and transactions. PostgreSQL follows a traditional table-based data model, making it suitable for applications that require structured data and complex relationships.
Another key difference is in their consistency models. Apache Cassandra uses a tunable consistency model, allowing developers to choose between strong consistency or eventual consistency based on application requirements. PostgreSQL, on the other hand, provides strong consistency by default, ensuring immediate consistency across all nodes in a distributed system.
See also: Top 10 Big Data platforms
Apache Cassandra is a highly scalable and distributed NoSQL database designed for handling large amounts of data across multiple commodity servers. It follows a wide-column data model and provides high availability and fault tolerance through its masterless architecture. Cassandra is known for its ability to handle massive write and read workloads, making it suitable for applications that require high scalability and low-latency data access. However, it sacrifices some features of traditional databases, such as complex joins and transactions, in favor of scalability and performance.
PostgreSQL, on the other hand, is a powerful relational database management system (RDBMS) known for its robustness and compliance with the SQL standard. It supports ACID (Atomicity, Consistency, Isolation, Durability) properties and offers a wide range of advanced features, including complex queries, joins, and transactions. PostgreSQL follows a traditional table-based data model, making it suitable for applications that require structured data and complex relationships.
Another key difference is in their consistency models. Apache Cassandra uses a tunable consistency model, allowing developers to choose between strong consistency or eventual consistency based on application requirements. PostgreSQL, on the other hand, provides strong consistency by default, ensuring immediate consistency across all nodes in a distributed system.
See also: Top 10 Big Data platforms
