RethinkDB vs ArangoDB

Compare features, pricing, and capabilities to find which solution is best for your needs.

RethinkDB icon

RethinkDB

RethinkDB is a free and open-source, distributed document database designed for building real-time web applications.

Open Source
Platforms: Mac OS X Windows Linux BSD Discontinued
Screenshots:
VS
ArangoDB icon

ArangoDB

ArangoDB is a highly scalable, multi-model NoSQL database that natively combines document, graph, and key/value data models in a single core. It supports ACID transactions across all data types and offers robust features for developers building complex, data-intensive applications. by triAGENS GmbH

Open Source
Platforms: Mac OS X Windows Linux
Screenshots:

Comparison Summary

RethinkDB and ArangoDB are both powerful solutions in their space. RethinkDB offers rethinkdb is a free and open-source, distributed document database designed for building real-time web applications., while ArangoDB provides arangodb is a highly scalable, multi-model nosql database that natively combines document, graph, and key/value data models in a single core. it supports acid transactions across all data types and offers robust features for developers building complex, data-intensive applications.. Compare their features and pricing to find the best match for your needs.

Pros & Cons Comparison

RethinkDB

RethinkDB

Analysis & Comparison

Advantages

Excellent real-time data pushing capabilities (changefeeds).
Elegant and programmatic query language (ReQL).
Flexible JSON document model.
Designed for distributed deployments and scalability.
Active open-source community maintaining the project.

Limitations

Original commercial company is no longer operational.
Reliance on community for support and future development.
Smaller ecosystem compared to larger databases like MongoDB or PostgreSQL.
Steeper learning curve for ReQL compared to SQL for some developers.
ArangoDB

ArangoDB

Analysis & Comparison

Advantages

Native multi-model (document, graph, key/value) in a single core.
ACID transactions across different data models.
Powerful and flexible query language (AQL).
Designed for horizontal scalability and high availability.
Simplifies development for applications with interconnected data.

Limitations

Learning curve for understanding the multi-model approach and optimizing AQL.
Community support is growing but may not be as mature as some single-model databases.
Performance optimization might require specific knowledge of the multi-model architecture.

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