What are the most common data consistency models for column-family NoSQL databases?

1 Eventual consistency

Eventual consistency is a data consistency model that allows temporary inconsistencies between different copies of the same data, as long as they converge to the same state over time. This means that when you write or update data in one node of the database, it may not be immediately visible or accessible in other nodes, until they synchronize with each other. Eventual consistency is often used by column-family NoSQL databases that prioritize availability and partition tolerance over consistency, such as Cassandra and DynamoDB. Eventual consistency can improve the responsiveness and scalability of your applications, but it can also introduce uncertainty and complexity when dealing with concurrent or conflicting updates.

2 Strong consistency

Strong consistency is a data consistency model that ensures that all copies of the same data are always in sync, and that any read operation returns the most recent write operation. This means that when you write or update data in one node of the database, it is immediately propagated and reflected in all other nodes, and any subsequent read operation will return the same value. Strong consistency is often used by column-family NoSQL databases that prioritize consistency and availability over partition tolerance, such as HBase and Google Bigtable. Strong consistency can guarantee the accuracy and reliability of your data, but it can also increase the latency and reduce the availability of your applications, especially in the event of network failures or partitions.

3 Tunable consistency

Tunable consistency is a data consistency model that allows you to choose the level of consistency that suits your application needs, depending on the type and importance of the data and the query. This means that you can specify different consistency levels for different operations, such as strong, eventual, quorum, or local consistency. Tunable consistency is often used by column-family NoSQL databases that offer flexibility and control over the trade-offs between consistency, availability, and partition tolerance, such as Cassandra and Scylla. Tunable consistency can help you balance the performance and quality of your applications, but it can also require more configuration and testing to ensure optimal results.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?