Amazon DynamoDB vs Azure Cosmos DB
Comprehensive side-by-side comparison of Amazon DynamoDB vs Azure Cosmos DB including features, integrations, customer segments, supported platforms, pros & cons, and company details. Find the best nosql database software solution for your business needs.
Product Comparison
Amazon DynamoDB
DynamoDB: Scalable NoSQL Database for Modern Applications
Azure Cosmos DB
Globally Distributed, Multi-Model Database Service
Description
Amazon DynamoDB is a fully managed, serverless, key-value and document database designed for high-performance applications at any scale. It provides consistent single-digit millisecond latency, and seamlessly scales to handle even the most dem...
Description
Azure Cosmos DB is a fully managed, globally distributed, multi-model database service designed for modern application development. It offers guaranteed low latency, high availability, and elastic scalability. Supporting multiple data models –...
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Use Cases
Use Cases
Made For
Made For
Key Features
- Data Replication
- Access Controls/Permissions
- Data Storage Management
- Backup and Recovery
- Multiple Programming Languages Supported
- Database Conversion
Key Features
- Object Oriented Database
- For NoSQL Databases
- Data Retrieval
- Automatic Backup
- Access Controls/Permissions
- Data Storage Management
Industries
- Gaming
- E-commerce
- Ad Tech
- Mobile Applications
- IoT
Industries
- Retail
- Gaming
- IoT
- Financial Services
- Healthcare
Customer Segments
- Small Businesses
- Mid-size Businesses
- Large Enterprises
Customer Segments
- Small Businesses
- Mid-size Businesses
- Large Enterprises
Supported Platforms
- Web
- Mobile
Supported Platforms
- Web
- Mobile
Pros
- Exceptional Scalability: Handles massive workloads without performance degradation.
- Fully Managed Service: Reduces operational overhead and simplifies database management.
- High Availability and Durability: Ensures data is always accessible and protected.
- Flexible Schema: Allows for rapid development and iteration without rigid schema constraints.
Cons
- Complexity of Data Modeling: Requires careful planning to optimize performance and cost.
- Limited Query Capabilities: Compared to relational databases, querying can be more complex for certain use cases.
Pros
- Globally distributed with low latency
- Multi-model database support for flexibility
- Elastic scalability to handle fluctuating workloads
- Comprehensive security features and compliance certifications
- Seamless integration with other Azure services
Cons
- Can be complex to optimize costs due to provisioned throughput model
- Vendor lock-in to the Azure ecosystem