Apache Cassandra vs Datomic

Struggling to choose between Apache Cassandra and Datomic? Both products offer unique advantages, making it a tough decision.

Apache Cassandra is a Databases solution with tags like distributed, scalable, high-availability, fault-tolerant, wide-column-store.

It boasts features such as Distributed database system, Linear scalability, Fault tolerance, Tunable consistency, Column-oriented database, Multi-datacenter replication and pros including High availability, Fast writes, Tunable consistency, Flexible schema design, Linear scalability.

On the other hand, Datomic is a Development product tagged with distributed, datalog, acid, temporal, flexible-data-modeling, scalable.

Its standout features include Distributed database, Uses Datalog query language, ACID transactions, Temporal/historical database capabilities, Flexible schema design, Scalable across multiple servers, and it shines with pros like Handles large datasets and scales horizontally, Flexible schema allows for evolving data models, Query performance optimized for reads, Built-in caching improves read speeds, ACID transactions ensure data consistency, Temporal querying enables data auditing.

Feature	Apache Cassandra	Datomic
Overall Score	1	N/A
Primary Category	Databases	Development

Product Overview

Apache Cassandra

Description: Apache Cassandra is a free, open-source, distributed NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

Datomic

Description: Datomic is a distributed database designed to enable scalable, flexible and intelligent applications. It uses Datalog and transaction processing to provide ACID transactions, temporal database capabilities and flexible data modeling. Datomic is well suited for applications that need to manage large data sets across multiple servers.

Key Features Comparison

Apache Cassandra Features

• Distributed database system
• Linear scalability
• Fault tolerance
• Tunable consistency
• Column-oriented database
• Multi-datacenter replication

Datomic Features

• Distributed database
• Uses Datalog query language
• ACID transactions
• Temporal/historical database capabilities
• Flexible schema design
• Scalable across multiple servers

Pros & Cons Analysis

Apache Cassandra

Pros

• High availability
• Fast writes
• Tunable consistency
• Flexible schema design
• Linear scalability

Cons

• Eventual consistency only
• Complex data modeling
• No joins or transactions
• Limited query capabilities
• Steep learning curve

Datomic

Pros

• Handles large datasets and scales horizontally
• Flexible schema allows for evolving data models
• Query performance optimized for reads
• Built-in caching improves read speeds
• ACID transactions ensure data consistency
• Temporal querying enables data auditing

Cons

• Not ideal for OLTP workloads
• Limited ad-hoc querying capabilities
• Proprietary query language has learning curve
• Hosted cloud option only available on AWS

Pricing Comparison

Apache Cassandra

• Open Source

Datomic

• Subscription-Based
• Pay-As-You-Go