Amazon DynamoDB vs RocksDB: What are the differences?

Introduction

In this article, we will compare Amazon DynamoDB and RocksDB, two popular database systems. We will highlight the key differences between them and provide a brief description of each difference.

1. Data Model: Amazon DynamoDB is a NoSQL database that supports document, key-value, and wide-column data models. It allows flexible schema design and is suitable for applications that require high scalability. On the other hand, RocksDB is a key-value store database that follows a simple key-value data model. It is optimized for read-heavy workloads and offers high-performance data storage and retrieval.

2. Data Distribution and Scalability: DynamoDB is a fully managed distributed database that automatically partitions data across multiple servers for high availability and scalability. It transparently handles the distribution of data and workload across these servers. In contrast, RocksDB operates as a single-node database and does not provide built-in mechanisms for data distribution or scaling. It can be used as a component within a larger distributed system.

3. Consistency Models: DynamoDB offers both strong consistency and eventual consistency models. Strong consistency ensures that all reads reflect the latest write, while eventual consistency allows for faster and more scalable operations at the cost of potential data inconsistency. RocksDB, on the other hand, does not provide built-in support for consistency models. Consistency needs to be implemented at the application level when using RocksDB.

4. Data Persistence: DynamoDB automatically replicates data across multiple data centers for durability and fault tolerance. It provides a managed service that takes care of data persistence. In contrast, RocksDB is an in-memory database and requires additional measures like write-ahead logs or persistent storage engines to ensure data persistence and durability.

5. Indexing and Querying: DynamoDB supports secondary indexes, allowing efficient querying of data based on different attributes. It also provides a query language for filtering and sorting data. RocksDB, being a key-value store, does not provide native support for secondary indexes or complex querying. Querying in RocksDB is primarily based on key lookups or range scans.

6. Transaction Support: DynamoDB supports atomic transactions that provide consistency and isolation guarantees. It allows developers to group multiple operations into a transaction and ensures that they are either all executed or none are. RocksDB, being an embedded database, does not offer built-in transaction support. Transactional behavior needs to be implemented manually by the application when using RocksDB.

In summary, Amazon DynamoDB and RocksDB differ in terms of their data models, data distribution and scalability, consistency models, data persistence, indexing and querying capabilities, and transaction support. DynamoDB provides a managed, scalable, and highly available distributed database service, while RocksDB is optimized for high-performance key-value storage in single-node environments.