Amazon DynamoDB
Architecture
YugabyteDB: A distributed SQL database similar to Google Spanner. It offers strong consistency, ACID transactions, and supports SQL. It's great for applications that need relational data integrity, complex transactions, hybrid cloud setups, and deployments across multiple regions.
DynamoDB: A NoSQL key-value store focused on high performance and scalability. It uses eventual consistency and works well for key-value or document-based data with predictable access patterns. It's often used in web applications, caching, and systems that require large-scale, fast operations.
SQL compatibility
YugabyteDB: Fully compatible with PostgreSQL, allowing you to use familiar SQL queries and tools.
DynamoDB: Doesn't support SQL directly and requires learning its own query language.
Data model and APIs
YugabyteDB: Supports multiple APIs, including YSQL (compatible with PostgreSQL) for relational data and YCQL for wide-column data storage. This gives flexibility in handling different types of data.
DynamoDB: A schemaless key-value and document (JSON) database that uses a proprietary API.
Consistency
YugabyteDB: Provides strong consistency with distributed ACID transactions, ensuring data integrity across nodes. YSQL only supports strong consistency, while YCQL supports both strong and eventual consistency.
DynamoDB: Uses eventual consistency by default, but offers the option for strong consistency on reads. It doesn't provide strong consistency across the board.
Transactions
YugabyteDB: Fully supports distributed ACID transactions across tables, rows, and columns, making it ideal for complex transactional operations. Transactions are consistent across regions and handled efficiently.
DynamoDB: Offers limited transaction support. Transactions are only available within a single partition key, making it less ideal for complex transactions. ACID guarantees apply only within the same region, and transactions are capped at 100 items.
Indexes
YugabyteDB: Indexes are globally consistent and updated transactionally. The query optimizer automatically selects the best way to execute queries with or without an index.
DynamoDB: Indexes are eventually consistent. Strongly consistent reads are only possible on local indexes, and global indexes support only eventual consistency. Queries or scans must be manually optimized as there is no query optimizer.
Performance and Scalability
YugabyteDB: Built for high performance with low-latency and high throughput. It supports horizontal scaling with auto-sharding for growth.
DynamoDB: Optimized for fast, high-volume workloads. It scales well but performance depends on how you configure read/write capacity. Works best for simple key-value tasks but may struggle with complex transactions.
Deployment Model
YugabyteDB: Can be deployed on-premises, in private data centers, or across cloud providers (AWS, GCP, Azure), giving you more control over your setup and costs.
DynamoDB: Fully managed by AWS and can only run within their ecosystem, limiting flexibility for hybrid or multi-cloud setups.
Costs
YugabyteDB: Costs depend on your infrastructure if self-hosted or based on usage if managed. It offers better cost control as you can optimize based on your hardware and deployment choices. Being open source, the software itself doesn't have inherent costs.
DynamoDB: Costs are based on the number of read and write requests, storage, and optional features like backups. It's cost-effective if your workload is predictable, but on-demand pricing can get expensive with sudden traffic spikes.