ArangoDB vs Cassandra: What are the differences?
Introduction
When considering database management systems for a project, ArangoDB and Cassandra are two popular options. While both are NoSQL databases, they have key differences that should be considered before making a decision.
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Data Model: ArangoDB is a multi-model database that supports key-value pairs, documents, and graphs within a single query interface, making it versatile for different data structures. On the other hand, Cassandra follows a column-family data model, which is ideal for handling large amounts of data with high availability and partition tolerance but may be more limited in terms of data structure flexibility.
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Query Language: ArangoDB uses its query language, AQL (ArangoDB Query Language), which allows for complex queries across different data models. In contrast, Cassandra uses CQL (Cassandra Query Language), a SQL-like language that is optimized for querying high-volume, low-latency data.
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Consistency Model: ArangoDB supports both strong and eventual consistency levels, giving users the flexibility to choose the level of consistency needed for their application. On the other hand, Cassandra offers tunable consistency, allowing users to choose between strong, eventual, and other consistency levels based on their requirements.
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Scalability: ArangoDB is horizontally scalable, meaning it can distribute data across multiple nodes to handle growing amounts of data and traffic. Cassandra, on the other hand, is known for its linear scalability, making it a popular choice for large-scale distributed systems that require seamless scaling.
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Fault Tolerance: ArangoDB provides automatic sharding and replication for data redundancy and fault tolerance, ensuring data availability even in the case of node failures. In comparison, Cassandra is designed with fault tolerance in mind, using a masterless architecture and peer-to-peer communication to prevent any single point of failure.
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Use Cases: ArangoDB is suitable for applications that require flexibility in data modeling and complex queries across different data types, such as social networks and content management systems. In contrast, Cassandra is best suited for use cases that prioritize high availability, partition tolerance, and linear scalability, such as real-time analytics and messaging platforms.
In Summary, ArangoDB and Cassandra differ in aspects such as data model flexibility, query language, consistency levels, scalability options, fault tolerance mechanisms, and ideal use cases.
