YugabyteDB vs Cassandra

Get distributed ACID transactions and dynamic queries. Benefit from superior TCO and seamless scaling. Ready to switch to YugabyteDB’s Cassandra-inspired API?

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Why Choose YugabyteDB vs Cassandra


Strong Data Consistency

YugabyteDB offers distributed ACID transactions, guaranteeing applications access the latest data, unlike Cassandra’s eventually consistent system which risks stale reads, data loss, and resurrected deleted values.

Rapid Horizontal Scaling

YugabyteDB enables quick online scaling, populating new nodes with compressed data, while Cassandra faces delays due to complex node bootstrapping and rebalancing.

High Resource Utilization

YugabyteDB boasts higher data density and usable storage per node, reducing clusters and hardware costs, while Cassandra’s low data density of 1-2 TB per node demands up to 10x more servers.

Powerful Queries

YugabyteDB offers a unified database with multiple APIs. Harness the power of advanced SQL queries with YSQL, adapting your apps seamlessly while utilizing the same core database and infrastructure.
Query Language
Cassandra Query Language (CQL)
Cassandra-inspired API and fully compatible PostgreSQL API
Native JSON
ACID Transactions
Cluster Expansion
Complex and time-consuming
Quick and non-disruptive
Upgrade Methods
Time-consuming based on volume of data
Quick with zero downtime
Ad Hoc Queries
Difficult and usually requires duplicate table
Seamlessly supported
Replication Options
Asynchronous replication with tunable consistency levels
Synchronous and xCluster asynchronous replication
Data Density
1-2 TB per node
5-10 TB per node

Benefits of YugabyteDB vs Cassandra

YugabyteDB is the only open source, multi-cloud, multi-API, distributed database designed for mission-critical applications. Its modern, cloud native architecture provides three key advantages over Cassandra.

Faster Productivity

Use well-known APIs, with built-in resilience and scale, to rapidly create apps and promptly address new demands.

Lower Total Cost of Ownership

Pack more into each node and handle data better. The result…fewer clusters and lower hardware costs (up to 10x).

Improved Efficiency

Scale faster, shrink cluster sizes, and consolidate databases effortlessly.

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