White Paper
Transcending the Constraints of DynamoDB with Fauna
Overview
While DynamoDB has proven effective as a key-value store, its rigid data model, limited querying capabilities, and complex partition management create challenges as applications scale and evolve. Fauna’s Document-Relational model solves these issues by combining the scalability of a document database with the powerful querying, consistency, and flexibility of relational databases, offering a modern solution for evolving application needs.
Key takeaways
Powerful, Flexible Querying: Fauna provides a rich query language with native support for joins and relationships, eliminating the need for DynamoDB’s workarounds like denormalization and complex index management.
True Serverless Architecture: Fauna delivers a fully serverless experience with no provisioning, scaling, or partitioning concerns, unlike DynamoDB, where partition key design and capacity management can become bottlenecks.
Seamless Schema Evolution: Fauna allows schema enforcement that can evolve with your application, compared to DynamoDB’s need for rigid upfront planning and limited schema flexibility.
Strong Consistency by Default: Fauna ensures strong consistency across distributed regions, addressing DynamoDB’s eventual consistency model, which often complicates global applications and multi-region consistency.
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