Amazon DynamoDB vs Azure Cosmos DB vs Google Cloud Firestore: NoSQL Services Compared

Amazon DynamoDB vs Azure Cosmos DB vs Google Cloud Firestore: NoSQL Services Compared
Amazon DynamoDB vs Azure Cosmos DB vs Google Cloud Firestore: NoSQL Services Compared | Image credit: Pexel

NoSQL databases are essential in modern cloud applications where scalability, performance, and flexible data models are crucial. AWS, Azure, and GCP each offer robust managed NoSQL database services with unique strengths and architectures. In this article, we compare Amazon DynamoDB, Azure Cosmos DB, and Google Cloud Firestore — three fully managed NoSQL databases designed for speed, scale, and developer productivity.

Key features of Amazon DynamoDB

  • Key-value and document database with single-digit millisecond latency
  • Fully managed, serverless, with on-demand or provisioned capacity modes
  • Built-in replication across AWS Regions for global apps
  • Integrated with AWS IAM, VPC, KMS, and Lambda for security and extensibility
  • Supports PartiQL for SQL-like querying and rich indexing
  • Global tables for multi-region active-active architecture
  • Amazon DynamoDB Documentation

Key features of Azure Cosmos DB

  • Globally distributed multi-model NoSQL database
  • Supports document (Core API), key-value (Table API), graph (Gremlin), and column-family (Cassandra)
  • Automatic and manual indexing options with tunable consistency
  • Guaranteed < 10ms read/write latency at the 99th percentile
  • Five well-defined consistency levels including strong and eventual
  • Seamless integration with Azure Functions, Synapse, and Logic Apps
  • Azure Cosmos DB Documentation

Key features of Google Cloud Firestore

  • Flexible, scalable document database for mobile, web, and server apps
  • Real-time sync and offline support for mobile SDKs
  • Strong consistency and hierarchical data organization
  • Seamless Firebase integration and GCP IAM support
  • Supports regional and multi-region deployments with automatic scaling
  • Uses structured query language with robust client SDKs
  • Google Cloud Firestore Documentation

What is similar in Amazon DynamoDB vs Azure Cosmos DB vs Google Cloud Firestore

  • All are fully managed NoSQL services optimized for scale and performance
  • Provide automatic scaling and high availability by default
  • Offer SDKs and APIs for seamless integration into applications
  • Support for JSON-based or key-value/document data models
  • Integration with serverless platforms and event-driven architecture
  • Enable encryption at rest and integration with IAM for secure access control

What is different in Amazon DynamoDB vs Azure Cosmos DB vs Google Cloud Firestore

  • Data Model Support: Cosmos DB is multi-model (Core, Cassandra, Gremlin), whereas DynamoDB and Firestore focus on document/key-value types
  • Query Capabilities: Firestore supports structured queries and indexes automatically; DynamoDB uses PartiQL and GSI/LSI; Cosmos DB offers advanced SQL-like queries
  • Consistency Models: Cosmos DB stands out with 5 levels of consistency, DynamoDB uses eventual or strongly consistent reads, Firestore uses strong consistency by default
  • Global Distribution: Cosmos DB offers turnkey global distribution with multiple write regions; DynamoDB provides global tables; Firestore supports multi-region deployments
  • Use Cases: Firestore excels in real-time mobile/web apps, Cosmos DB in enterprise-scale multi-model workloads, and DynamoDB in scalable microservices or serverless stacks

Conclusion

Each cloud vendor offers a powerful NoSQL solution tailored to specific workload demands. DynamoDB is a great fit for ultra-low latency applications with serverless backends. Cosmos DB provides unmatched versatility for enterprises needing multi-model support and finely tuned consistency. Firestore is optimized for real-time apps with seamless mobile and Firebase integration. The best choice depends on your architecture’s scaling needs, query patterns, and operational expectations.

Location: India

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